diff --git a/.github/workflows/cmake.yml b/.github/workflows/cmake.yml
index a53bf8ae..e5c6e206 100644
--- a/.github/workflows/cmake.yml
+++ b/.github/workflows/cmake.yml
@@ -30,7 +30,8 @@ jobs:
       - name: Configure CMake
         # Configure CMake in a 'build' subdirectory. `CMAKE_BUILD_TYPE` is only required if you are using a single-configuration generator such as make.
         # See https://cmake.org/cmake/help/latest/variable/CMAKE_BUILD_TYPE.html?highlight=cmake_build_type
-        run: cmake -B ${{github.workspace}}/build -DCMAKE_BUILD_TYPE=${{env.BUILD_TYPE}} -DCMAKE_PREFIX_PATH='/usr/local/lib/python3.10/dist-packages/torch/share/cmake'
+        # Note: Skip dataset copy as datasets are now in sageData repository
+        run: cmake -B ${{github.workspace}}/build -DCMAKE_BUILD_TYPE=${{env.BUILD_TYPE}} -DCMAKE_PREFIX_PATH='/usr/local/lib/python3.10/dist-packages/torch/share/cmake' -DLIBAMM_SKIP_DATASET_COPY=ON
 
       - name: Build
         # Build your program with the given configuration
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 54ba1dbe..83188a63 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -163,6 +163,20 @@ file(COPY ${allCopyFiles} DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/benchmark/scri
 file(COPY ${allCopyFiles} DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/benchmark/scripts)
 
 # copy files needed for real world matrix loader
-set(source_directory "${CMAKE_SOURCE_DIR}/benchmark/datasets/")
-set(destination_directory "${CMAKE_BINARY_DIR}/benchmark/datasets/")
-file(COPY ${source_directory} DESTINATION ${destination_directory})
+# Allow external projects to specify dataset path or disable dataset copy
+option(LIBAMM_SKIP_DATASET_COPY "Skip copying benchmark datasets" OFF)
+set(LIBAMM_DATASET_SOURCE_DIR "${CMAKE_SOURCE_DIR}/benchmark/datasets" CACHE PATH "Path to LibAMM benchmark datasets")
+
+if(NOT LIBAMM_SKIP_DATASET_COPY)
+    if(EXISTS "${LIBAMM_DATASET_SOURCE_DIR}")
+        message(STATUS "Copying LibAMM datasets from: ${LIBAMM_DATASET_SOURCE_DIR}")
+        set(source_directory "${LIBAMM_DATASET_SOURCE_DIR}/")
+        set(destination_directory "${CMAKE_BINARY_DIR}/benchmark/datasets/")
+        file(COPY ${source_directory} DESTINATION ${destination_directory})
+    else()
+        message(STATUS "LibAMM datasets not found at ${LIBAMM_DATASET_SOURCE_DIR}, skipping dataset copy")
+        message(STATUS "Set LIBAMM_DATASET_SOURCE_DIR to specify a different path, or set LIBAMM_SKIP_DATASET_COPY=ON to disable")
+    endif()
+else()
+    message(STATUS "LibAMM dataset copy disabled (LIBAMM_SKIP_DATASET_COPY=ON)")
+endif()
diff --git a/benchmark/datasets/AST/README.md b/benchmark/datasets/AST/README.md
deleted file mode 100644
index 09aa38a8..00000000
--- a/benchmark/datasets/AST/README.md
+++ /dev/null
@@ -1,5 +0,0 @@
-AST: Astrophysics,
- Nonlinear radiative transfer and statistical equilibrium in astrophysics
-Atom=Fe, Atmos=M65GXM
-https://math.nist.gov/MatrixMarket/data/Harwell-Boeing/astroph/astroph.html
-
diff --git a/benchmark/datasets/AST/mcfe.mtx b/benchmark/datasets/AST/mcfe.mtx
deleted file mode 100644
index 7324de23..00000000
--- a/benchmark/datasets/AST/mcfe.mtx
+++ /dev/null
@@ -1,24384 +0,0 @@
-%%MatrixMarket matrix coordinate real general
-765 765 24382
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diff --git a/benchmark/datasets/BUS/README.md b/benchmark/datasets/BUS/README.md
deleted file mode 100644
index 13096ae5..00000000
--- a/benchmark/datasets/BUS/README.md
+++ /dev/null
@@ -1,4 +0,0 @@
-BUS: Optimal power flow problems Power flow in 2400 bus system in western US
-Jacobian matrix for an approximately 2400 bus system in the Western United States. The rows represent the equality and some nonlinear constraints of the power flow problem. The first block of columns represents the standard angle and voltage variables of the power flow problem. The last block of columns is very sparse and represents the transformer taps and capacitors.
-https://math.nist.gov/MatrixMarket/data/Harwell-Boeing/gemat/gemat1.html
-
diff --git a/benchmark/datasets/BUS/gemat1.mtx b/benchmark/datasets/BUS/gemat1.mtx
deleted file mode 100644
index 06f6c85f..00000000
--- a/benchmark/datasets/BUS/gemat1.mtx
+++ /dev/null
@@ -1,47371 +0,0 @@
-%%MatrixMarket matrix coordinate real general
-4929 10595 47369
-1 1  3.5059583000000e+00
-2 1 -1.1963116000000e+00
-5 1 -8.1771007000000e-01
-6 1  2.9102284000000e-01
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diff --git a/benchmark/datasets/DWAVE/README.md b/benchmark/datasets/DWAVE/README.md
deleted file mode 100644
index 81948953..00000000
--- a/benchmark/datasets/DWAVE/README.md
+++ /dev/null
@@ -1,11 +0,0 @@
-DWAVE: Dielectric channel waveguide problems arise in many integrated circuit applications. (IC)
-eads to the nonsymmetric eigenvalue problem of the form
-
-C H = beta^2 B H
-where C11 and C22 are penta- or tri-diagonal matrices, C12 and C21 are (tri-)diagonal matrices, and B11 and B22 are nonsingular diagonal matrices. This generalized eigenvalue problem is reduced to a standard eigenvalue problem, A x=x lambda, where A=B^(-1), since B is diagonal.
-
-The computational task is to determine the right most eigenvalues and their corresponding eigenvectors. In some cases, there are eigenvalues with a negative real part several orders of magnitude larger than the desired eigenvalues with positive real part. This problem presents a challenge to existing numerical methods.
-
-Note that DWA512 and DWB512 are matrices of the same order which correspond to different parameter values.
-https://math.nist.gov/MatrixMarket/data/NEP/dwave/dwave.html
-
diff --git a/benchmark/datasets/DWAVE/dwa512.mtx b/benchmark/datasets/DWAVE/dwa512.mtx
deleted file mode 100644
index dcdaf750..00000000
--- a/benchmark/datasets/DWAVE/dwa512.mtx
+++ /dev/null
@@ -1,2482 +0,0 @@
-%%MatrixMarket matrix coordinate real general
-512 512 2480
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diff --git a/benchmark/datasets/DWAVE/dwb512.mtx b/benchmark/datasets/DWAVE/dwb512.mtx
deleted file mode 100644
index 96e757ac..00000000
--- a/benchmark/datasets/DWAVE/dwb512.mtx
+++ /dev/null
@@ -1,2502 +0,0 @@
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diff --git a/benchmark/datasets/ECO/README.md b/benchmark/datasets/ECO/README.md
deleted file mode 100644
index 890a88a3..00000000
--- a/benchmark/datasets/ECO/README.md
+++ /dev/null
@@ -1,4 +0,0 @@
-ECO: Economic Models
-One of fifteen regions in world economic model.
-https://math.nist.gov/MatrixMarket/data/Harwell-Boeing/econiea/wm3.html
-
diff --git a/benchmark/datasets/ECO/document.pdf b/benchmark/datasets/ECO/document.pdf
deleted file mode 100644
index ce45589b..00000000
Binary files a/benchmark/datasets/ECO/document.pdf and /dev/null differ
diff --git a/benchmark/datasets/ECO/wm2.mtx b/benchmark/datasets/ECO/wm2.mtx
deleted file mode 100644
index 7076bc07..00000000
--- a/benchmark/datasets/ECO/wm2.mtx
+++ /dev/null
@@ -1,2944 +0,0 @@
-%%MatrixMarket matrix coordinate real general
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diff --git a/benchmark/datasets/ECO/wm3.mtx b/benchmark/datasets/ECO/wm3.mtx
deleted file mode 100644
index a46b269a..00000000
--- a/benchmark/datasets/ECO/wm3.mtx
+++ /dev/null
@@ -1,2950 +0,0 @@
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diff --git a/benchmark/datasets/MNIST/README.md b/benchmark/datasets/MNIST/README.md
deleted file mode 100644
index 6f4c6d32..00000000
--- a/benchmark/datasets/MNIST/README.md
+++ /dev/null
@@ -1,2 +0,0 @@
-60000 training 28*28 handwritten digits
-http://yann.lecun.com/exdb/mnist/
diff --git a/benchmark/datasets/MNIST/train-images.idx3-ubyte b/benchmark/datasets/MNIST/train-images.idx3-ubyte
deleted file mode 100644
index bbce2765..00000000
Binary files a/benchmark/datasets/MNIST/train-images.idx3-ubyte and /dev/null differ
diff --git a/benchmark/datasets/MediaMill/MediaMill.pth b/benchmark/datasets/MediaMill/MediaMill.pth
deleted file mode 100644
index 5958f9d4..00000000
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diff --git a/benchmark/datasets/MediaMill/step1RSaveCsv.ipynb b/benchmark/datasets/MediaMill/step1RSaveCsv.ipynb
deleted file mode 100644
index b1f5c1c7..00000000
--- a/benchmark/datasets/MediaMill/step1RSaveCsv.ipynb
+++ /dev/null
@@ -1,723 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "vscode": {
-     "languageId": "r"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "if(!require('mldr.datasets')) {\n",
-    "    install.packages('mldr.datasets')\n",
-    "    library('mldr.datasets')\n",
-    "}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "vscode": {
-     "languageId": "r"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Looking for datasetmediamillin the download directory\n",
-      "\n",
-      "\n",
-      "Now reading datasetmediamill\n",
-      "\n",
-      "\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<span style=white-space:pre-wrap>'@inproceedings{,\\n  title = \"The challenge problem for automated detection of 101 semantic concepts in multimedia\",\\n  author = \"Snoek, C. G. M. and Worring, M. and van Gemert, J. C. and Geusebroek, J. M. and Smeulders, A. W. M.\",\\n  booktitle = \"Proc. 14th ACM International Conference on Multimedia, MULTIMEDIA06,\\n  year = \"2006\",\\n  pages = \"421--430\"\\n}'</span>"
-      ],
-      "text/latex": [
-       "'@inproceedings\\{,\\textbackslash{}n  title = \"The challenge problem for automated detection of 101 semantic concepts in multimedia\",\\textbackslash{}n  author = \"Snoek, C. G. M. and Worring, M. and van Gemert, J. C. and Geusebroek, J. M. and Smeulders, A. W. M.\",\\textbackslash{}n  booktitle = \"Proc. 14th ACM International Conference on Multimedia, MULTIMEDIA06,\\textbackslash{}n  year = \"2006\",\\textbackslash{}n  pages = \"421--430\"\\textbackslash{}n\\}'"
-      ],
-      "text/markdown": [
-       "<span style=white-space:pre-wrap>'@inproceedings{,\\n  title = \"The challenge problem for automated detection of 101 semantic concepts in multimedia\",\\n  author = \"Snoek, C. G. M. and Worring, M. and van Gemert, J. C. and Geusebroek, J. M. and Smeulders, A. W. M.\",\\n  booktitle = \"Proc. 14th ACM International Conference on Multimedia, MULTIMEDIA06,\\n  year = \"2006\",\\n  pages = \"421--430\"\\n}'</span>"
-      ],
-      "text/plain": [
-       "[1] \"@inproceedings{,\\n  title = \\\"The challenge problem for automated detection of 101 semantic concepts in multimedia\\\",\\n  author = \\\"Snoek, C. G. M. and Worring, M. and van Gemert, J. C. and Geusebroek, J. M. and Smeulders, A. W. M.\\\",\\n  booktitle = \\\"Proc. 14th ACM International Conference on Multimedia, MULTIMEDIA06,\\n  year = \\\"2006\\\",\\n  pages = \\\"421--430\\\"\\n}\""
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<dl>\n",
-       "\t<dt>$num.attributes</dt>\n",
-       "\t\t<dd>221</dd>\n",
-       "\t<dt>$num.instances</dt>\n",
-       "\t\t<dd>43907</dd>\n",
-       "\t<dt>$num.inputs</dt>\n",
-       "\t\t<dd>120</dd>\n",
-       "\t<dt>$num.labels</dt>\n",
-       "\t\t<dd>101</dd>\n",
-       "\t<dt>$num.labelsets</dt>\n",
-       "\t\t<dd>6555</dd>\n",
-       "\t<dt>$num.single.labelsets</dt>\n",
-       "\t\t<dd>4104</dd>\n",
-       "\t<dt>$max.frequency</dt>\n",
-       "\t\t<dd>2363</dd>\n",
-       "\t<dt>$cardinality</dt>\n",
-       "\t\t<dd>4.37556653836518</dd>\n",
-       "\t<dt>$density</dt>\n",
-       "\t\t<dd>0.0433224409739127</dd>\n",
-       "\t<dt>$meanIR</dt>\n",
-       "\t\t<dd>256.404697696982</dd>\n",
-       "\t<dt>$scumble</dt>\n",
-       "\t\t<dd>0.354673996119894</dd>\n",
-       "\t<dt>$scumble.cv</dt>\n",
-       "\t\t<dd>0.742560523110413</dd>\n",
-       "\t<dt>$tcs</dt>\n",
-       "\t\t<dd>18.1905956558211</dd>\n",
-       "</dl>\n"
-      ],
-      "text/latex": [
-       "\\begin{description}\n",
-       "\\item[\\$num.attributes] 221\n",
-       "\\item[\\$num.instances] 43907\n",
-       "\\item[\\$num.inputs] 120\n",
-       "\\item[\\$num.labels] 101\n",
-       "\\item[\\$num.labelsets] 6555\n",
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-       "\\item[\\$max.frequency] 2363\n",
-       "\\item[\\$cardinality] 4.37556653836518\n",
-       "\\item[\\$density] 0.0433224409739127\n",
-       "\\item[\\$meanIR] 256.404697696982\n",
-       "\\item[\\$scumble] 0.354673996119894\n",
-       "\\item[\\$scumble.cv] 0.742560523110413\n",
-       "\\item[\\$tcs] 18.1905956558211\n",
-       "\\end{description}\n"
-      ],
-      "text/markdown": [
-       "$num.attributes\n",
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-       ":   120\n",
-       "$num.labels\n",
-       ":   101\n",
-       "$num.labelsets\n",
-       ":   6555\n",
-       "$num.single.labelsets\n",
-       ":   4104\n",
-       "$max.frequency\n",
-       ":   2363\n",
-       "$cardinality\n",
-       ":   4.37556653836518\n",
-       "$density\n",
-       ":   0.0433224409739127\n",
-       "$meanIR\n",
-       ":   256.404697696982\n",
-       "$scumble\n",
-       ":   0.354673996119894\n",
-       "$scumble.cv\n",
-       ":   0.742560523110413\n",
-       "$tcs\n",
-       ":   18.1905956558211\n",
-       "\n",
-       "\n"
-      ],
-      "text/plain": [
-       "$num.attributes\n",
-       "[1] 221\n",
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-       "$num.instances\n",
-       "[1] 43907\n",
-       "\n",
-       "$num.inputs\n",
-       "[1] 120\n",
-       "\n",
-       "$num.labels\n",
-       "[1] 101\n",
-       "\n",
-       "$num.labelsets\n",
-       "[1] 6555\n",
-       "\n",
-       "$num.single.labelsets\n",
-       "[1] 4104\n",
-       "\n",
-       "$max.frequency\n",
-       "[1] 2363\n",
-       "\n",
-       "$cardinality\n",
-       "[1] 4.375567\n",
-       "\n",
-       "$density\n",
-       "[1] 0.04332244\n",
-       "\n",
-       "$meanIR\n",
-       "[1] 256.4047\n",
-       "\n",
-       "$scumble\n",
-       "[1] 0.354674\n",
-       "\n",
-       "$scumble.cv\n",
-       "[1] 0.7425605\n",
-       "\n",
-       "$tcs\n",
-       "[1] 18.1906\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "mediamill <- mediamill()  # Check and load the dataset\n",
-    "toBibtex(mediamill)\n",
-    "mediamill$measures"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "vscode": {
-     "languageId": "r"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<style>\n",
-       ".list-inline {list-style: none; margin:0; padding: 0}\n",
-       ".list-inline>li {display: inline-block}\n",
-       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
-       "</style>\n",
-       "<ol class=list-inline><li>'name'</li><li>'dataset'</li><li>'attributesIndexes'</li><li>'attributes'</li><li>'labels'</li><li>'labelsets'</li><li>'measures'</li><li>'bibtex'</li></ol>\n"
-      ],
-      "text/latex": [
-       "\\begin{enumerate*}\n",
-       "\\item 'name'\n",
-       "\\item 'dataset'\n",
-       "\\item 'attributesIndexes'\n",
-       "\\item 'attributes'\n",
-       "\\item 'labels'\n",
-       "\\item 'labelsets'\n",
-       "\\item 'measures'\n",
-       "\\item 'bibtex'\n",
-       "\\end{enumerate*}\n"
-      ],
-      "text/markdown": [
-       "1. 'name'\n",
-       "2. 'dataset'\n",
-       "3. 'attributesIndexes'\n",
-       "4. 'attributes'\n",
-       "5. 'labels'\n",
-       "6. 'labelsets'\n",
-       "7. 'measures'\n",
-       "8. 'bibtex'\n",
-       "\n",
-       "\n"
-      ],
-      "text/plain": [
-       "[1] \"name\"              \"dataset\"           \"attributesIndexes\"\n",
-       "[4] \"attributes\"        \"labels\"            \"labelsets\"        \n",
-       "[7] \"measures\"          \"bibtex\"           "
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "names(mediamill)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "vscode": {
-     "languageId": "r"
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-   },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "'data.frame'"
-      ],
-      "text/latex": [
-       "'data.frame'"
-      ],
-      "text/markdown": [
-       "'data.frame'"
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-      "text/plain": [
-       "[1] \"data.frame\""
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "class(mediamill$dataset)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "vscode": {
-     "languageId": "r"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
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-       " Mean   :0.44136   Mean   :0.46176   Mean   :0.45032   Mean   :0.3717  \n",
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-       " Median :0.17843   Median :0.29485   Median :0.21553   Median :0.55615  \n",
-       " Mean   :0.19049   Mean   :0.29626   Mean   :0.22290   Mean   :0.54135  \n",
-       " 3rd Qu.:0.23012   3rd Qu.:0.32997   3rd Qu.:0.26412   3rd Qu.:0.59640  \n",
-       " Max.   :0.56908   Max.   :0.47418   Max.   :0.53162   Max.   :0.66624  \n",
-       "     Att17             Att18             Att19             Att20       \n",
-       " Min.   :0.04823   Min.   :0.03415   Min.   :0.04948   Min.   :0.0179  \n",
-       " 1st Qu.:0.53655   1st Qu.:0.51386   1st Qu.:0.41228   1st Qu.:0.2364  \n",
-       " Median :0.58147   Median :0.58752   Median :0.47004   Median :0.2906  \n",
-       " Mean   :0.56529   Mean   :0.56425   Mean   :0.46581   Mean   :0.3039  \n",
-       " 3rd Qu.:0.61525   3rd Qu.:0.63655   3rd Qu.:0.52611   3rd Qu.:0.3585  \n",
-       " Max.   :0.71333   Max.   :0.72899   Max.   :0.70010   Max.   :0.6699  \n",
-       "     Att21             Att22            Att23             Att24        \n",
-       " Min.   :0.04343   Min.   :0.0433   Min.   :0.03945   Min.   :0.02922  \n",
-       " 1st Qu.:0.40426   1st Qu.:0.3722   1st Qu.:0.53128   1st Qu.:0.36496  \n",
-       " Median :0.44365   Median :0.4130   Median :0.58177   Median :0.42052  \n",
-       " Mean   :0.43854   Mean   :0.4052   Mean   :0.56374   Mean   :0.41530  \n",
-       " 3rd Qu.:0.48093   3rd Qu.:0.4477   3rd Qu.:0.61936   3rd Qu.:0.47040  \n",
-       " Max.   :0.61075   Max.   :0.5653   Max.   :0.70081   Max.   :0.62966  \n",
-       "     Att25             Att26              Att27             Att28        \n",
-       " Min.   :0.02036   Min.   :0.003989   Min.   :0.01473   Min.   :0.01027  \n",
-       " 1st Qu.:0.32983   1st Qu.:0.070644   1st Qu.:0.22699   1st Qu.:0.18189  \n",
-       " Median :0.39241   Median :0.099601   Median :0.29390   Median :0.23929  \n",
-       " Mean   :0.38855   Mean   :0.118823   Mean   :0.30880   Mean   :0.25848  \n",
-       " 3rd Qu.:0.45103   3rd Qu.:0.141270   3rd Qu.:0.37621   3rd Qu.:0.31380  \n",
-       " Max.   :0.61264   Max.   :0.673797   Max.   :0.67551   Max.   :0.70587  \n",
-       "     Att29             Att30             Att31             Att32        \n",
-       " Min.   :0.04378   Min.   :0.01545   Min.   :0.03367   Min.   :0.04133  \n",
-       " 1st Qu.:0.33247   1st Qu.:0.22349   1st Qu.:0.36553   1st Qu.:0.33656  \n",
-       " Median :0.37315   Median :0.27923   Median :0.40088   Median :0.38659  \n",
-       " Mean   :0.37452   Mean   :0.29202   Mean   :0.39102   Mean   :0.37215  \n",
-       " 3rd Qu.:0.41795   3rd Qu.:0.34662   3rd Qu.:0.42826   3rd Qu.:0.42350  \n",
-       " Max.   :0.59206   Max.   :0.67039   Max.   :0.51320   Max.   :0.53390  \n",
-       "     Att33             Att34             Att35             Att36        \n",
-       " Min.   :0.02983   Min.   :0.04345   Min.   :0.01839   Min.   :0.03948  \n",
-       " 1st Qu.:0.28622   1st Qu.:0.32135   1st Qu.:0.23883   1st Qu.:0.34110  \n",
-       " Median :0.33526   Median :0.37603   Median :0.28622   Median :0.37291  \n",
-       " Mean   :0.32514   Mean   :0.36344   Mean   :0.28607   Mean   :0.36370  \n",
-       " 3rd Qu.:0.37634   3rd Qu.:0.41763   3rd Qu.:0.33281   3rd Qu.:0.39755  \n",
-       " Max.   :0.49580   Max.   :0.53612   Max.   :0.50731   Max.   :0.47432  \n",
-       "     Att37             Att38             Att39             Att40        \n",
-       " Min.   :0.03855   Min.   :0.03553   Min.   :0.02616   Min.   :0.01891  \n",
-       " 1st Qu.:0.26927   1st Qu.:0.32728   1st Qu.:0.31189   1st Qu.:0.27706  \n",
-       " Median :0.31507   Median :0.37729   Median :0.34434   Median :0.31521  \n",
-       " Mean   :0.30385   Mean   :0.36332   Mean   :0.33848   Mean   :0.30876  \n",
-       " 3rd Qu.:0.34912   3rd Qu.:0.41511   3rd Qu.:0.37247   3rd Qu.:0.34746  \n",
-       " Max.   :0.42736   Max.   :0.49942   Max.   :0.45129   Max.   :0.43799  \n",
-       "     Att41              Att42             Att43             Att44        \n",
-       " Min.   :0.003869   Min.   :0.01495   Min.   :0.01119   Min.   :0.03845  \n",
-       " 1st Qu.:0.079875   1st Qu.:0.22823   1st Qu.:0.18787   1st Qu.:0.31099  \n",
-       " Median :0.112425   Median :0.28258   Median :0.24063   Median :0.33617  \n",
-       " Mean   :0.125596   Mean   :0.28366   Mean   :0.24615   Mean   :0.33378  \n",
-       " 3rd Qu.:0.154999   3rd Qu.:0.33756   3rd Qu.:0.29826   3rd Qu.:0.36201  \n",
-       " Max.   :0.550583   Max.   :0.54573   Max.   :0.54248   Max.   :0.45181  \n",
-       "     Att45             Att46             Att47             Att48       \n",
-       " Min.   :0.01566   Min.   :0.08501   Min.   :0.07718   Min.   :0.0534  \n",
-       " 1st Qu.:0.22605   1st Qu.:0.64912   1st Qu.:0.63424   1st Qu.:0.5828  \n",
-       " Median :0.27475   Median :0.67732   Median :0.66751   Median :0.6262  \n",
-       " Mean   :0.27512   Mean   :0.66509   Mean   :0.65555   Mean   :0.6136  \n",
-       " 3rd Qu.:0.32297   3rd Qu.:0.69619   3rd Qu.:0.69204   3rd Qu.:0.6591  \n",
-       " Max.   :0.50823   Max.   :0.73541   Max.   :0.76018   Max.   :0.7618  \n",
-       "     Att49             Att50             Att51             Att52        \n",
-       " Min.   :0.08093   Min.   :0.03704   Min.   :0.09156   Min.   :0.07086  \n",
-       " 1st Qu.:0.61620   1st Qu.:0.53216   1st Qu.:0.59559   1st Qu.:0.51917  \n",
-       " Median :0.65919   Median :0.59251   Median :0.62334   Median :0.55679  \n",
-       " Mean   :0.64494   Mean   :0.57867   Mean   :0.61442   Mean   :0.54511  \n",
-       " 3rd Qu.:0.69207   3rd Qu.:0.64060   3rd Qu.:0.64507   3rd Qu.:0.58392  \n",
-       " Max.   :0.76997   Max.   :0.76649   Max.   :0.71084   Max.   :0.66595  \n",
-       "     Att53             Att54             Att55            Att56        \n",
-       " Min.   :0.06063   Min.   :0.05769   Min.   :0.0451   Min.   :0.00757  \n",
-       " 1st Qu.:0.61603   1st Qu.:0.57778   1st Qu.:0.5580   1st Qu.:0.25209  \n",
-       " Median :0.64904   Median :0.61481   Median :0.6023   Median :0.35153  \n",
-       " Mean   :0.63978   Mean   :0.60434   Mean   :0.5873   Mean   :0.36831  \n",
-       " 3rd Qu.:0.67602   3rd Qu.:0.64200   3rd Qu.:0.6319   3rd Qu.:0.47400  \n",
-       " Max.   :0.74979   Max.   :0.71907   Max.   :0.7011   Max.   :0.75953  \n",
-       "     Att57             Att58             Att59             Att60        \n",
-       " Min.   :0.02934   Min.   :0.02154   Min.   :0.08694   Min.   :0.03032  \n",
-       " 1st Qu.:0.54944   1st Qu.:0.48242   1st Qu.:0.59023   1st Qu.:0.50990  \n",
-       " Median :0.61138   Median :0.56070   Median :0.62329   Median :0.57294  \n",
-       " Mean   :0.59060   Mean   :0.54385   Mean   :0.61348   Mean   :0.55929  \n",
-       " 3rd Qu.:0.65513   3rd Qu.:0.62152   3rd Qu.:0.64831   3rd Qu.:0.62258  \n",
-       " Max.   :0.74405   Max.   :0.77933   Max.   :0.73110   Max.   :0.76104  \n",
-       "     Att61             Att62             Att63             Att64        \n",
-       " Min.   :0.02163   Min.   :0.04026   Min.   :0.03979   Min.   :0.04418  \n",
-       " 1st Qu.:0.36419   1st Qu.:0.42767   1st Qu.:0.44313   1st Qu.:0.37880  \n",
-       " Median :0.41009   Median :0.46533   Median :0.49585   Median :0.42109  \n",
-       " Mean   :0.40247   Mean   :0.45076   Mean   :0.47596   Mean   :0.41610  \n",
-       " 3rd Qu.:0.45108   3rd Qu.:0.49411   3rd Qu.:0.53154   3rd Qu.:0.46176  \n",
-       " Max.   :0.52910   Max.   :0.58242   Max.   :0.61053   Max.   :0.59927  \n",
-       "     Att65              Att66             Att67             Att68       \n",
-       " Min.   :0.007951   Min.   :0.02768   Min.   :0.04509   Min.   :0.0359  \n",
-       " 1st Qu.:0.143129   1st Qu.:0.33986   1st Qu.:0.26841   1st Qu.:0.4299  \n",
-       " Median :0.176729   Median :0.37063   Median :0.29424   Median :0.4692  \n",
-       " Mean   :0.186521   Mean   :0.36579   Mean   :0.29115   Mean   :0.4554  \n",
-       " 3rd Qu.:0.217942   3rd Qu.:0.39986   3rd Qu.:0.31890   3rd Qu.:0.4994  \n",
-       " Max.   :0.474277   Max.   :0.49702   Max.   :0.41698   Max.   :0.5759  \n",
-       "     Att69             Att70             Att71              Att72        \n",
-       " Min.   :0.01747   Min.   :0.01175   Min.   :0.002431   Min.   :0.01202  \n",
-       " 1st Qu.:0.25782   1st Qu.:0.23364   1st Qu.:0.049986   1st Qu.:0.21352  \n",
-       " Median :0.29729   Median :0.27653   Median :0.065536   Median :0.25981  \n",
-       " Mean   :0.29512   Mean   :0.27538   Mean   :0.073017   Mean   :0.26610  \n",
-       " 3rd Qu.:0.33619   3rd Qu.:0.31888   3rd Qu.:0.085986   3rd Qu.:0.31299  \n",
-       " Max.   :0.44585   Max.   :0.42905   Max.   :0.349518   Max.   :0.51986  \n",
-       "     Att73              Att74             Att75              Att76       \n",
-       " Min.   :0.004767   Min.   :0.01944   Min.   :0.007156   Min.   :0.0285  \n",
-       " 1st Qu.:0.097774   1st Qu.:0.26654   1st Qu.:0.139927   1st Qu.:0.4487  \n",
-       " Median :0.125696   Median :0.30362   Median :0.174237   Median :0.5015  \n",
-       " Mean   :0.136845   Mean   :0.30256   Mean   :0.182529   Mean   :0.4909  \n",
-       " 3rd Qu.:0.161017   3rd Qu.:0.34199   3rd Qu.:0.214633   3rd Qu.:0.5452  \n",
-       " Max.   :0.476783   Max.   :0.46324   Max.   :0.453655   Max.   :0.6211  \n",
-       "     Att77             Att78             Att79            Att80        \n",
-       " Min.   :0.05519   Min.   :0.05528   Min.   :0.0567   Min.   :0.01015  \n",
-       " 1st Qu.:0.52124   1st Qu.:0.54859   1st Qu.:0.4680   1st Qu.:0.18475  \n",
-       " Median :0.55556   Median :0.59508   Median :0.5154   Median :0.23194  \n",
-       " Mean   :0.54467   Mean   :0.57667   Mean   :0.5099   Mean   :0.24817  \n",
-       " 3rd Qu.:0.58410   3rd Qu.:0.62577   3rd Qu.:0.5609   3rd Qu.:0.29377  \n",
-       " Max.   :0.68379   Max.   :0.69540   Max.   :0.6965   Max.   :0.58982  \n",
-       "     Att81             Att82             Att83             Att84        \n",
-       " Min.   :0.03395   Min.   :0.05571   Min.   :0.04722   Min.   :0.02211  \n",
-       " 1st Qu.:0.41737   1st Qu.:0.33363   1st Qu.:0.52099   1st Qu.:0.31923  \n",
-       " Median :0.45115   Median :0.36162   Median :0.55807   Median :0.36833  \n",
-       " Mean   :0.44510   Mean   :0.35845   Mean   :0.54717   Mean   :0.36681  \n",
-       " 3rd Qu.:0.48101   3rd Qu.:0.38794   3rd Qu.:0.58803   3rd Qu.:0.41697  \n",
-       " Max.   :0.57362   Max.   :0.48762   Max.   :0.67298   Max.   :0.55539  \n",
-       "     Att85             Att86              Att87             Att88         \n",
-       " Min.   :0.01557   Min.   :0.003154   Min.   :0.01512   Min.   :0.005934  \n",
-       " 1st Qu.:0.29550   1st Qu.:0.066917   1st Qu.:0.27262   1st Qu.:0.129379  \n",
-       " Median :0.34910   Median :0.089510   Median :0.33491   Median :0.168758  \n",
-       " Mean   :0.34958   Mean   :0.103700   Mean   :0.34297   Mean   :0.188072  \n",
-       " 3rd Qu.:0.40359   3rd Qu.:0.122882   3rd Qu.:0.40723   3rd Qu.:0.225267  \n",
-       " Max.   :0.55468   Max.   :0.507578   Max.   :0.62994   Max.   :0.605335  \n",
-       "     Att89             Att90             Att91             Att92        \n",
-       " Min.   :0.02432   Min.   :0.00921   Min.   :0.02658   Min.   :0.04424  \n",
-       " 1st Qu.:0.33487   1st Qu.:0.18134   1st Qu.:0.35031   1st Qu.:0.31300  \n",
-       " Median :0.38193   Median :0.22762   Median :0.37704   Median :0.35478  \n",
-       " Mean   :0.38026   Mean   :0.24134   Mean   :0.37014   Mean   :0.34197  \n",
-       " 3rd Qu.:0.42967   3rd Qu.:0.28584   3rd Qu.:0.39930   3rd Qu.:0.38473  \n",
-       " Max.   :0.57142   Max.   :0.58083   Max.   :0.47192   Max.   :0.48307  \n",
-       "     Att93            Att94             Att95             Att96        \n",
-       " Min.   :0.0391   Min.   :0.04803   Min.   :0.01035   Min.   :0.03617  \n",
-       " 1st Qu.:0.2924   1st Qu.:0.33923   1st Qu.:0.20714   1st Qu.:0.33809  \n",
-       " Median :0.3365   Median :0.38783   Median :0.24824   Median :0.36619  \n",
-       " Mean   :0.3251   Mean   :0.37423   Mean   :0.25001   Mean   :0.35682  \n",
-       " 3rd Qu.:0.3703   3rd Qu.:0.42211   3rd Qu.:0.29014   3rd Qu.:0.38639  \n",
-       " Max.   :0.4795   Max.   :0.53773   Max.   :0.45101   Max.   :0.45285  \n",
-       "     Att97             Att98             Att99             Att100       \n",
-       " Min.   :0.04816   Min.   :0.04682   Min.   :0.02157   Min.   :0.01513  \n",
-       " 1st Qu.:0.25861   1st Qu.:0.30671   1st Qu.:0.29686   1st Qu.:0.26219  \n",
-       " Median :0.29187   Median :0.34208   Median :0.32311   Median :0.29410  \n",
-       " Mean   :0.28322   Mean   :0.33250   Mean   :0.31835   Mean   :0.28889  \n",
-       " 3rd Qu.:0.31571   3rd Qu.:0.37028   3rd Qu.:0.34524   3rd Qu.:0.32022  \n",
-       " Max.   :0.39719   Max.   :0.46586   Max.   :0.43092   Max.   :0.40240  \n",
-       "     Att101             Att102            Att103             Att104       \n",
-       " Min.   :0.003232   Min.   :0.01529   Min.   :0.006317   Min.   :0.02516  \n",
-       " 1st Qu.:0.083724   1st Qu.:0.27851   1st Qu.:0.151224   1st Qu.:0.31581  \n",
-       " Median :0.108706   Median :0.32088   Median :0.189627   Median :0.34059  \n",
-       " Mean   :0.116058   Mean   :0.31744   Mean   :0.195857   Mean   :0.33586  \n",
-       " 3rd Qu.:0.139389   3rd Qu.:0.35945   3rd Qu.:0.232958   3rd Qu.:0.36131  \n",
-       " Max.   :0.410732   Max.   :0.48495   Max.   :0.443334   Max.   :0.43252  \n",
-       "     Att105             Att106            Att107           Att108       \n",
-       " Min.   :0.009409   Min.   :0.09577   Min.   :0.1080   Min.   :0.08332  \n",
-       " 1st Qu.:0.199994   1st Qu.:0.60809   1st Qu.:0.5832   1st Qu.:0.56611  \n",
-       " Median :0.239571   Median :0.63113   Median :0.6162   Median :0.60307  \n",
-       " Mean   :0.240770   Mean   :0.62187   Mean   :0.6046   Mean   :0.59131  \n",
-       " 3rd Qu.:0.279060   3rd Qu.:0.64645   3rd Qu.:0.6404   3rd Qu.:0.63033  \n",
-       " Max.   :0.429334   Max.   :0.68389   Max.   :0.7252   Max.   :0.71515  \n",
-       "     Att109           Att110            Att111           Att112      \n",
-       " Min.   :0.1189   Min.   :0.03229   Min.   :0.1286   Min.   :0.1201  \n",
-       " 1st Qu.:0.6209   1st Qu.:0.46127   1st Qu.:0.5776   1st Qu.:0.4868  \n",
-       " Median :0.6554   Median :0.52166   Median :0.6009   Median :0.5149  \n",
-       " Mean   :0.6413   Mean   :0.50827   Mean   :0.5931   Mean   :0.5044  \n",
-       " 3rd Qu.:0.6798   3rd Qu.:0.56659   3rd Qu.:0.6179   3rd Qu.:0.5352  \n",
-       " Max.   :0.7481   Max.   :0.68559   Max.   :0.6691   Max.   :0.6026  \n",
-       "     Att113           Att114            Att115            Att116       \n",
-       " Min.   :0.1015   Min.   :0.06539   Min.   :0.05588   Min.   :0.01023  \n",
-       " 1st Qu.:0.5525   1st Qu.:0.53613   1st Qu.:0.51142   1st Qu.:0.22933  \n",
-       " Median :0.5860   Median :0.56440   Median :0.54709   Median :0.28867  \n",
-       " Mean   :0.5793   Mean   :0.55721   Mean   :0.53595   Mean   :0.29512  \n",
-       " 3rd Qu.:0.6139   3rd Qu.:0.58598   3rd Qu.:0.57202   3rd Qu.:0.35440  \n",
-       " Max.   :0.6993   Max.   :0.65028   Max.   :0.63502   Max.   :0.73271  \n",
-       "     Att117            Att118            Att119            Att120       \n",
-       " Min.   :0.04805   Min.   :0.01724   Min.   :0.07929   Min.   :0.02673  \n",
-       " 1st Qu.:0.55311   1st Qu.:0.37776   1st Qu.:0.57569   1st Qu.:0.43834  \n",
-       " Median :0.59416   Median :0.44268   Median :0.60304   Median :0.49439  \n",
-       " Mean   :0.58187   Mean   :0.43193   Mean   :0.59405   Mean   :0.48530  \n",
-       " 3rd Qu.:0.62416   3rd Qu.:0.49400   3rd Qu.:0.62175   3rd Qu.:0.54123  \n",
-       " Max.   :0.69179   Max.   :0.72876   Max.   :0.67240   Max.   :0.69077  \n",
-       "     Class1             Class2             Class3           Class4        \n",
-       " Min.   :0.000000   Min.   :0.000000   Min.   :0.0000   Min.   :0.000000  \n",
-       " 1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.0000   1st Qu.:0.000000  \n",
-       " Median :0.000000   Median :0.000000   Median :0.0000   Median :0.000000  \n",
-       " Mean   :0.009748   Mean   :0.001549   Mean   :0.0502   Mean   :0.009702  \n",
-       " 3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.0000   3rd Qu.:0.000000  \n",
-       " Max.   :1.000000   Max.   :1.000000   Max.   :1.0000   Max.   :1.000000  \n",
-       "     Class5             Class6             Class7             Class8         \n",
-       " Min.   :0.000000   Min.   :0.000000   Min.   :0.000000   Min.   :0.0000000  \n",
-       " 1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.0000000  \n",
-       " Median :0.000000   Median :0.000000   Median :0.000000   Median :0.0000000  \n",
-       " Mean   :0.006969   Mean   :0.001298   Mean   :0.005853   Mean   :0.0007288  \n",
-       " 3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.0000000  \n",
-       " Max.   :1.000000   Max.   :1.000000   Max.   :1.000000   Max.   :1.0000000  \n",
-       "     Class9            Class10            Class11            Class12       \n",
-       " Min.   :0.000000   Min.   :0.000000   Min.   :0.000000   Min.   :0.00000  \n",
-       " 1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.00000  \n",
-       " Median :0.000000   Median :0.000000   Median :0.000000   Median :0.00000  \n",
-       " Mean   :0.001549   Mean   :0.001959   Mean   :0.007106   Mean   :0.08124  \n",
-       " 3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.00000  \n",
-       " Max.   :1.000000   Max.   :1.000000   Max.   :1.000000   Max.   :1.00000  \n",
-       "    Class13            Class14           Class15            Class16         \n",
-       " Min.   :0.000000   Min.   :0.00000   Min.   :0.000000   Min.   :0.0000000  \n",
-       " 1st Qu.:0.000000   1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.0000000  \n",
-       " Median :0.000000   Median :0.00000   Median :0.000000   Median :0.0000000  \n",
-       " Mean   :0.004897   Mean   :0.01296   Mean   :0.001435   Mean   :0.0008882  \n",
-       " 3rd Qu.:0.000000   3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.0000000  \n",
-       " Max.   :1.000000   Max.   :1.00000   Max.   :1.000000   Max.   :1.0000000  \n",
-       "    Class17           Class18            Class19            Class20        \n",
-       " Min.   :0.00000   Min.   :0.000000   Min.   :0.000000   Min.   :0.000000  \n",
-       " 1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.000000  \n",
-       " Median :0.00000   Median :0.000000   Median :0.000000   Median :0.000000  \n",
-       " Mean   :0.05181   Mean   :0.001207   Mean   :0.005922   Mean   :0.006833  \n",
-       " 3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.000000  \n",
-       " Max.   :1.00000   Max.   :1.000000   Max.   :1.000000   Max.   :1.000000  \n",
-       "    Class21             Class22           Class23           Class24        \n",
-       " Min.   :0.0000000   Min.   :0.00000   Min.   :0.00000   Min.   :0.000000  \n",
-       " 1st Qu.:0.0000000   1st Qu.:0.00000   1st Qu.:0.00000   1st Qu.:0.000000  \n",
-       " Median :0.0000000   Median :0.00000   Median :0.00000   Median :0.000000  \n",
-       " Mean   :0.0009566   Mean   :0.01068   Mean   :0.02198   Mean   :0.002323  \n",
-       " 3rd Qu.:0.0000000   3rd Qu.:0.00000   3rd Qu.:0.00000   3rd Qu.:0.000000  \n",
-       " Max.   :1.0000000   Max.   :1.00000   Max.   :1.00000   Max.   :1.000000  \n",
-       "    Class25          Class26            Class27           Class28        \n",
-       " Min.   :0.0000   Min.   :0.000000   Min.   :0.00000   Min.   :0.000000  \n",
-       " 1st Qu.:0.0000   1st Qu.:0.000000   1st Qu.:0.00000   1st Qu.:0.000000  \n",
-       " Median :0.0000   Median :0.000000   Median :0.00000   Median :0.000000  \n",
-       " Mean   :0.1285   Mean   :0.001389   Mean   :0.00993   Mean   :0.002118  \n",
-       " 3rd Qu.:0.0000   3rd Qu.:0.000000   3rd Qu.:0.00000   3rd Qu.:0.000000  \n",
-       " Max.   :1.0000   Max.   :1.000000   Max.   :1.00000   Max.   :1.000000  \n",
-       "    Class29            Class30          Class31            Class32      \n",
-       " Min.   :0.000000   Min.   :0.0000   Min.   :0.000000   Min.   :0.0000  \n",
-       " 1st Qu.:0.000000   1st Qu.:0.0000   1st Qu.:0.000000   1st Qu.:0.0000  \n",
-       " Median :0.000000   Median :0.0000   Median :0.000000   Median :0.0000  \n",
-       " Mean   :0.001093   Mean   :0.0023   Mean   :0.002391   Mean   :0.1756  \n",
-       " 3rd Qu.:0.000000   3rd Qu.:0.0000   3rd Qu.:0.000000   3rd Qu.:0.0000  \n",
-       " Max.   :1.000000   Max.   :1.0000   Max.   :1.000000   Max.   :1.0000  \n",
-       "    Class33            Class34          Class35           Class36        \n",
-       " Min.   :0.000000   Min.   :0.0000   Min.   :0.00000   Min.   :0.000000  \n",
-       " 1st Qu.:0.000000   1st Qu.:0.0000   1st Qu.:0.00000   1st Qu.:0.000000  \n",
-       " Median :0.000000   Median :1.0000   Median :0.00000   Median :0.000000  \n",
-       " Mean   :0.006787   Mean   :0.6363   Mean   :0.03715   Mean   :0.003986  \n",
-       " 3rd Qu.:0.000000   3rd Qu.:1.0000   3rd Qu.:0.00000   3rd Qu.:0.000000  \n",
-       " Max.   :1.000000   Max.   :1.0000   Max.   :1.00000   Max.   :1.000000  \n",
-       "    Class37            Class38           Class39            Class40       \n",
-       " Min.   :0.000000   Min.   :0.00000   Min.   :0.000000   Min.   :0.00000  \n",
-       " 1st Qu.:0.000000   1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.00000  \n",
-       " Median :0.000000   Median :0.00000   Median :0.000000   Median :0.00000  \n",
-       " Mean   :0.002255   Mean   :0.01218   Mean   :0.009247   Mean   :0.00599  \n",
-       " 3rd Qu.:0.000000   3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.00000  \n",
-       " Max.   :1.000000   Max.   :1.00000   Max.   :1.000000   Max.   :1.00000  \n",
-       "    Class41            Class42            Class43            Class44       \n",
-       " Min.   :0.000000   Min.   :0.000000   Min.   :0.000000   Min.   :0.00000  \n",
-       " 1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.00000  \n",
-       " Median :0.000000   Median :0.000000   Median :0.000000   Median :0.00000  \n",
-       " Mean   :0.002528   Mean   :0.002687   Mean   :0.002482   Mean   :0.08917  \n",
-       " 3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.00000  \n",
-       " Max.   :1.000000   Max.   :1.000000   Max.   :1.000000   Max.   :1.00000  \n",
-       "    Class45           Class46            Class47             Class48       \n",
-       " Min.   :0.00000   Min.   :0.000000   Min.   :0.0000000   Min.   :0.00000  \n",
-       " 1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.0000000   1st Qu.:0.00000  \n",
-       " Median :0.00000   Median :0.000000   Median :0.0000000   Median :0.00000  \n",
-       " Mean   :0.03066   Mean   :0.008085   Mean   :0.0008655   Mean   :0.00123  \n",
-       " 3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.0000000   3rd Qu.:0.00000  \n",
-       " Max.   :1.00000   Max.   :1.000000   Max.   :1.0000000   Max.   :1.00000  \n",
-       "    Class49             Class50           Class51            Class52      \n",
-       " Min.   :0.0000000   Min.   :0.00000   Min.   :0.000000   Min.   :0.0000  \n",
-       " 1st Qu.:0.0000000   1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.0000  \n",
-       " Median :0.0000000   Median :0.00000   Median :0.000000   Median :0.0000  \n",
-       " Mean   :0.0008882   Mean   :0.00312   Mean   :0.003211   Mean   :0.2007  \n",
-       " 3rd Qu.:0.0000000   3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.0000  \n",
-       " Max.   :1.0000000   Max.   :1.00000   Max.   :1.000000   Max.   :1.0000  \n",
-       "    Class53            Class54            Class55          Class56       \n",
-       " Min.   :0.000000   Min.   :0.000000   Min.   :0.0000   Min.   :0.00000  \n",
-       " 1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.0000   1st Qu.:0.00000  \n",
-       " Median :0.000000   Median :0.000000   Median :0.0000   Median :0.00000  \n",
-       " Mean   :0.002095   Mean   :0.002551   Mean   :0.0473   Mean   :0.01171  \n",
-       " 3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.0000   3rd Qu.:0.00000  \n",
-       " Max.   :1.000000   Max.   :1.000000   Max.   :1.0000   Max.   :1.00000  \n",
-       "    Class57           Class58           Class59           Class60         \n",
-       " Min.   :0.00000   Min.   :0.00000   Min.   :0.00000   Min.   :0.0000000  \n",
-       " 1st Qu.:0.00000   1st Qu.:0.00000   1st Qu.:0.00000   1st Qu.:0.0000000  \n",
-       " Median :0.00000   Median :0.00000   Median :0.00000   Median :0.0000000  \n",
-       " Mean   :0.04628   Mean   :0.04858   Mean   :0.02877   Mean   :0.0008427  \n",
-       " 3rd Qu.:0.00000   3rd Qu.:0.00000   3rd Qu.:0.00000   3rd Qu.:0.0000000  \n",
-       " Max.   :1.00000   Max.   :1.00000   Max.   :1.00000   Max.   :1.0000000  \n",
-       "    Class61           Class62            Class63            Class64        \n",
-       " Min.   :0.00000   Min.   :0.000000   Min.   :0.000000   Min.   :0.000000  \n",
-       " 1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.000000  \n",
-       " Median :0.00000   Median :0.000000   Median :0.000000   Median :0.000000  \n",
-       " Mean   :0.01455   Mean   :0.008427   Mean   :0.003006   Mean   :0.001161  \n",
-       " 3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.000000  \n",
-       " Max.   :1.00000   Max.   :1.000000   Max.   :1.000000   Max.   :1.000000  \n",
-       "    Class65           Class66          Class67          Class68      \n",
-       " Min.   :0.00000   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  \n",
-       " 1st Qu.:0.00000   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:1.0000  \n",
-       " Median :0.00000   Median :0.0000   Median :0.0000   Median :1.0000  \n",
-       " Mean   :0.01619   Mean   :0.3435   Mean   :0.3573   Mean   :0.7714  \n",
-       " 3rd Qu.:0.00000   3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:1.0000  \n",
-       " Max.   :1.00000   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  \n",
-       "    Class69           Class70            Class71            Class72        \n",
-       " Min.   :0.00000   Min.   :0.000000   Min.   :0.000000   Min.   :0.000000  \n",
-       " 1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.000000  \n",
-       " Median :0.00000   Median :0.000000   Median :0.000000   Median :0.000000  \n",
-       " Mean   :0.02574   Mean   :0.008791   Mean   :0.001708   Mean   :0.002984  \n",
-       " 3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.000000  \n",
-       " Max.   :1.00000   Max.   :1.000000   Max.   :1.000000   Max.   :1.000000  \n",
-       "    Class73             Class74            Class75             Class76       \n",
-       " Min.   :0.0000000   Min.   :0.000000   Min.   :0.0000000   Min.   :0.00000  \n",
-       " 1st Qu.:0.0000000   1st Qu.:0.000000   1st Qu.:0.0000000   1st Qu.:0.00000  \n",
-       " Median :0.0000000   Median :0.000000   Median :0.0000000   Median :0.00000  \n",
-       " Mean   :0.0009793   Mean   :0.002574   Mean   :0.0009338   Mean   :0.07416  \n",
-       " 3rd Qu.:0.0000000   3rd Qu.:0.000000   3rd Qu.:0.0000000   3rd Qu.:0.00000  \n",
-       " Max.   :1.0000000   Max.   :1.000000   Max.   :1.0000000   Max.   :1.00000  \n",
-       "    Class77          Class78             Class79          Class80       \n",
-       " Min.   :0.0000   Min.   :0.0000000   Min.   :0.0000   Min.   :0.00000  \n",
-       " 1st Qu.:0.0000   1st Qu.:0.0000000   1st Qu.:0.0000   1st Qu.:0.00000  \n",
-       " Median :0.0000   Median :0.0000000   Median :0.0000   Median :0.00000  \n",
-       " Mean   :0.0164   Mean   :0.0008655   Mean   :0.1095   Mean   :0.01426  \n",
-       " 3rd Qu.:0.0000   3rd Qu.:0.0000000   3rd Qu.:0.0000   3rd Qu.:0.00000  \n",
-       " Max.   :1.0000   Max.   :1.0000000   Max.   :1.0000   Max.   :1.00000  \n",
-       "    Class81            Class82           Class83            Class84       \n",
-       " Min.   :0.000000   Min.   :0.00000   Min.   :0.000000   Min.   :0.00000  \n",
-       " 1st Qu.:0.000000   1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.00000  \n",
-       " Median :0.000000   Median :0.00000   Median :0.000000   Median :0.00000  \n",
-       " Mean   :0.004418   Mean   :0.01264   Mean   :0.007857   Mean   :0.03423  \n",
-       " 3rd Qu.:0.000000   3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.00000  \n",
-       " Max.   :1.000000   Max.   :1.00000   Max.   :1.000000   Max.   :1.00000  \n",
-       "    Class85          Class86             Class87            Class88         \n",
-       " Min.   :0.0000   Min.   :0.0000000   Min.   :0.000000   Min.   :0.0000000  \n",
-       " 1st Qu.:0.0000   1st Qu.:0.0000000   1st Qu.:0.000000   1st Qu.:0.0000000  \n",
-       " Median :0.0000   Median :0.0000000   Median :0.000000   Median :0.0000000  \n",
-       " Mean   :0.1382   Mean   :0.0008655   Mean   :0.006787   Mean   :0.0008199  \n",
-       " 3rd Qu.:0.0000   3rd Qu.:0.0000000   3rd Qu.:0.000000   3rd Qu.:0.0000000  \n",
-       " Max.   :1.0000   Max.   :1.0000000   Max.   :1.000000   Max.   :1.0000000  \n",
-       "    Class89            Class90            Class91            Class92        \n",
-       " Min.   :0.000000   Min.   :0.000000   Min.   :0.000000   Min.   :0.000000  \n",
-       " 1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.000000  \n",
-       " Median :0.000000   Median :0.000000   Median :0.000000   Median :0.000000  \n",
-       " Mean   :0.004031   Mean   :0.001093   Mean   :0.007106   Mean   :0.007971  \n",
-       " 3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.000000  \n",
-       " Max.   :1.000000   Max.   :1.000000   Max.   :1.000000   Max.   :1.000000  \n",
-       "    Class93           Class94         Class95           Class96       \n",
-       " Min.   :0.00000   Min.   :0.000   Min.   :0.00000   Min.   :0.00000  \n",
-       " 1st Qu.:0.00000   1st Qu.:0.000   1st Qu.:0.00000   1st Qu.:0.00000  \n",
-       " Median :0.00000   Median :0.000   Median :0.00000   Median :0.00000  \n",
-       " Mean   :0.01123   Mean   :0.109   Mean   :0.04093   Mean   :0.07883  \n",
-       " 3rd Qu.:0.00000   3rd Qu.:0.000   3rd Qu.:0.00000   3rd Qu.:0.00000  \n",
-       " Max.   :1.00000   Max.   :1.000   Max.   :1.00000   Max.   :1.00000  \n",
-       "    Class97           Class98          Class99           Class100       \n",
-       " Min.   :0.00000   Min.   :0.0000   Min.   :0.00000   Min.   :0.000000  \n",
-       " 1st Qu.:0.00000   1st Qu.:0.0000   1st Qu.:0.00000   1st Qu.:0.000000  \n",
-       " Median :0.00000   Median :0.0000   Median :0.00000   Median :0.000000  \n",
-       " Mean   :0.08561   Mean   :0.1456   Mean   :0.02186   Mean   :0.000706  \n",
-       " 3rd Qu.:0.00000   3rd Qu.:0.0000   3rd Qu.:0.00000   3rd Qu.:0.000000  \n",
-       " Max.   :1.00000   Max.   :1.0000   Max.   :1.00000   Max.   :1.000000  \n",
-       "    Class101        .labelcount        .SCUMBLE     \n",
-       " Min.   :0.00000   Min.   : 0.000   Min.   :0.0000  \n",
-       " 1st Qu.:0.00000   1st Qu.: 3.000   1st Qu.:0.1596  \n",
-       " Median :0.00000   Median : 4.000   Median :0.3300  \n",
-       " Mean   :0.01066   Mean   : 4.376   Mean   :0.3547  \n",
-       " 3rd Qu.:0.00000   3rd Qu.: 6.000   3rd Qu.:0.5629  \n",
-       " Max.   :1.00000   Max.   :18.000   Max.   :0.9696  "
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "summary(mediamill$dataset)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "vscode": {
-     "languageId": "r"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "write.csv(mediamill$dataset, \"mediamill.csv\", row.names = FALSE)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "R",
-   "language": "R",
-   "name": "ir"
-  },
-  "language_info": {
-   "codemirror_mode": "r",
-   "file_extension": ".r",
-   "mimetype": "text/x-r-source",
-   "name": "R",
-   "pygments_lexer": "r",
-   "version": "4.3.1"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/benchmark/datasets/MediaMill/step2PythonSaveTensor.ipynb b/benchmark/datasets/MediaMill/step2PythonSaveTensor.ipynb
deleted file mode 100644
index 723447d4..00000000
--- a/benchmark/datasets/MediaMill/step2PythonSaveTensor.ipynb
+++ /dev/null
@@ -1,1038 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = pd.read_csv(\"mediamill.csv\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-       "      <th></th>\n",
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-       "      <th>...</th>\n",
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-       "      <td>0.508613</td>\n",
-       "      <td>0.505837</td>\n",
-       "      <td>0.437155</td>\n",
-       "      <td>0.490723</td>\n",
-       "      <td>0.262201</td>\n",
-       "      <td>0.459610</td>\n",
-       "      <td>0.393838</td>\n",
-       "      <td>0.524006</td>\n",
-       "      <td>0.370391</td>\n",
-       "      <td>0.329424</td>\n",
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-       "      <td>4</td>\n",
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-       "      <td>0.449571</td>\n",
-       "      <td>0.460490</td>\n",
-       "      <td>0.453469</td>\n",
-       "      <td>0.410779</td>\n",
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-       "      <td>0.402147</td>\n",
-       "      <td>0.349590</td>\n",
-       "      <td>0.536456</td>\n",
-       "      <td>0.318117</td>\n",
-       "      <td>0.301615</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
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-       "      <td>3</td>\n",
-       "      <td>0.206882</td>\n",
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-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>0.416800</td>\n",
-       "      <td>0.548996</td>\n",
-       "      <td>0.520850</td>\n",
-       "      <td>0.465410</td>\n",
-       "      <td>0.181603</td>\n",
-       "      <td>0.357255</td>\n",
-       "      <td>0.389347</td>\n",
-       "      <td>0.530189</td>\n",
-       "      <td>0.290942</td>\n",
-       "      <td>0.244521</td>\n",
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-       "      <th>4</th>\n",
-       "      <td>0.501986</td>\n",
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-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 223 columns</p>\n",
-       "</div>"
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-      "text/plain": [
-       "       Att1      Att2      Att3      Att4      Att5      Att6      Att7  \\\n",
-       "0  0.380877  0.494079  0.540009  0.422926  0.158318  0.326975  0.390861   \n",
-       "1  0.508613  0.505837  0.437155  0.490723  0.262201  0.459610  0.393838   \n",
-       "2  0.449571  0.460490  0.453469  0.410779  0.231759  0.402147  0.349590   \n",
-       "3  0.416800  0.548996  0.520850  0.465410  0.181603  0.357255  0.389347   \n",
-       "4  0.501986  0.480820  0.435543  0.432002  0.250599  0.408353  0.357816   \n",
-       "\n",
-       "       Att8      Att9     Att10  ...  Class94  Class95  Class96  Class97  \\\n",
-       "0  0.527121  0.254052  0.223731  ...        0        0        0        0   \n",
-       "1  0.524006  0.370391  0.329424  ...        0        0        0        0   \n",
-       "2  0.536456  0.318117  0.301615  ...        0        0        0        0   \n",
-       "3  0.530189  0.290942  0.244521  ...        0        0        0        0   \n",
-       "4  0.499186  0.353172  0.327622  ...        0        0        0        0   \n",
-       "\n",
-       "   Class98  Class99  Class100  Class101  .labelcount  .SCUMBLE  \n",
-       "0        0        0         0         0            4  0.273702  \n",
-       "1        0        0         0         0            4  0.703351  \n",
-       "2        0        0         0         0            3  0.206882  \n",
-       "3        0        0         0         0            3  0.395520  \n",
-       "4        0        0         0         0            3  0.206882  \n",
-       "\n",
-       "[5 rows x 223 columns]"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
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-       "      <td>0.511032</td>\n",
-       "      <td>0.463997</td>\n",
-       "      <td>0.202034</td>\n",
-       "      <td>0.492341</td>\n",
-       "      <td>0.317983</td>\n",
-       "      <td>0.547807</td>\n",
-       "      <td>0.393778</td>\n",
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-       "      <th>1</th>\n",
-       "      <td>0.508613</td>\n",
-       "      <td>0.505837</td>\n",
-       "      <td>0.437155</td>\n",
-       "      <td>0.490723</td>\n",
-       "      <td>0.262201</td>\n",
-       "      <td>0.459610</td>\n",
-       "      <td>0.393838</td>\n",
-       "      <td>0.524006</td>\n",
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-       "      <td>0.556555</td>\n",
-       "      <td>0.553718</td>\n",
-       "      <td>0.552479</td>\n",
-       "      <td>0.511739</td>\n",
-       "      <td>0.218366</td>\n",
-       "      <td>0.547476</td>\n",
-       "      <td>0.348174</td>\n",
-       "      <td>0.584991</td>\n",
-       "      <td>0.422205</td>\n",
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-       "      <th>2</th>\n",
-       "      <td>0.449571</td>\n",
-       "      <td>0.460490</td>\n",
-       "      <td>0.453469</td>\n",
-       "      <td>0.410779</td>\n",
-       "      <td>0.231759</td>\n",
-       "      <td>0.402147</td>\n",
-       "      <td>0.349590</td>\n",
-       "      <td>0.536456</td>\n",
-       "      <td>0.318117</td>\n",
-       "      <td>0.301615</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.627463</td>\n",
-       "      <td>0.539564</td>\n",
-       "      <td>0.638607</td>\n",
-       "      <td>0.496368</td>\n",
-       "      <td>0.480986</td>\n",
-       "      <td>0.199592</td>\n",
-       "      <td>0.535078</td>\n",
-       "      <td>0.323834</td>\n",
-       "      <td>0.571487</td>\n",
-       "      <td>0.397564</td>\n",
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-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>0.416800</td>\n",
-       "      <td>0.548996</td>\n",
-       "      <td>0.520850</td>\n",
-       "      <td>0.465410</td>\n",
-       "      <td>0.181603</td>\n",
-       "      <td>0.357255</td>\n",
-       "      <td>0.389347</td>\n",
-       "      <td>0.530189</td>\n",
-       "      <td>0.290942</td>\n",
-       "      <td>0.244521</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.604669</td>\n",
-       "      <td>0.557365</td>\n",
-       "      <td>0.571348</td>\n",
-       "      <td>0.565105</td>\n",
-       "      <td>0.497706</td>\n",
-       "      <td>0.252656</td>\n",
-       "      <td>0.546756</td>\n",
-       "      <td>0.346506</td>\n",
-       "      <td>0.589601</td>\n",
-       "      <td>0.430145</td>\n",
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-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>0.501986</td>\n",
-       "      <td>0.480820</td>\n",
-       "      <td>0.435543</td>\n",
-       "      <td>0.432002</td>\n",
-       "      <td>0.250599</td>\n",
-       "      <td>0.408353</td>\n",
-       "      <td>0.357816</td>\n",
-       "      <td>0.499186</td>\n",
-       "      <td>0.353172</td>\n",
-       "      <td>0.327622</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.607607</td>\n",
-       "      <td>0.543372</td>\n",
-       "      <td>0.566417</td>\n",
-       "      <td>0.526322</td>\n",
-       "      <td>0.484486</td>\n",
-       "      <td>0.186909</td>\n",
-       "      <td>0.564721</td>\n",
-       "      <td>0.325957</td>\n",
-       "      <td>0.578370</td>\n",
-       "      <td>0.398771</td>\n",
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-       "      <th>...</th>\n",
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-       "      <td>...</td>\n",
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-       "      <td>...</td>\n",
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-       "      <td>...</td>\n",
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-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
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-       "      <td>...</td>\n",
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-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
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-       "    <tr>\n",
-       "      <th>43902</th>\n",
-       "      <td>0.426864</td>\n",
-       "      <td>0.528629</td>\n",
-       "      <td>0.532957</td>\n",
-       "      <td>0.401551</td>\n",
-       "      <td>0.187178</td>\n",
-       "      <td>0.328457</td>\n",
-       "      <td>0.363949</td>\n",
-       "      <td>0.487699</td>\n",
-       "      <td>0.306376</td>\n",
-       "      <td>0.266459</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.610354</td>\n",
-       "      <td>0.544168</td>\n",
-       "      <td>0.553511</td>\n",
-       "      <td>0.580699</td>\n",
-       "      <td>0.559847</td>\n",
-       "      <td>0.348502</td>\n",
-       "      <td>0.587482</td>\n",
-       "      <td>0.488400</td>\n",
-       "      <td>0.624835</td>\n",
-       "      <td>0.527380</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>43903</th>\n",
-       "      <td>0.344094</td>\n",
-       "      <td>0.537319</td>\n",
-       "      <td>0.516101</td>\n",
-       "      <td>0.430633</td>\n",
-       "      <td>0.147998</td>\n",
-       "      <td>0.310974</td>\n",
-       "      <td>0.373041</td>\n",
-       "      <td>0.493417</td>\n",
-       "      <td>0.249852</td>\n",
-       "      <td>0.191468</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.582064</td>\n",
-       "      <td>0.527097</td>\n",
-       "      <td>0.581796</td>\n",
-       "      <td>0.555630</td>\n",
-       "      <td>0.515736</td>\n",
-       "      <td>0.271329</td>\n",
-       "      <td>0.520354</td>\n",
-       "      <td>0.410659</td>\n",
-       "      <td>0.564902</td>\n",
-       "      <td>0.453231</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>43904</th>\n",
-       "      <td>0.329709</td>\n",
-       "      <td>0.453422</td>\n",
-       "      <td>0.523771</td>\n",
-       "      <td>0.314048</td>\n",
-       "      <td>0.133553</td>\n",
-       "      <td>0.249196</td>\n",
-       "      <td>0.296952</td>\n",
-       "      <td>0.440839</td>\n",
-       "      <td>0.222037</td>\n",
-       "      <td>0.196553</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.574960</td>\n",
-       "      <td>0.522756</td>\n",
-       "      <td>0.594364</td>\n",
-       "      <td>0.567564</td>\n",
-       "      <td>0.524449</td>\n",
-       "      <td>0.232201</td>\n",
-       "      <td>0.554800</td>\n",
-       "      <td>0.408484</td>\n",
-       "      <td>0.570778</td>\n",
-       "      <td>0.453345</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>43905</th>\n",
-       "      <td>0.470031</td>\n",
-       "      <td>0.489588</td>\n",
-       "      <td>0.488227</td>\n",
-       "      <td>0.356816</td>\n",
-       "      <td>0.228900</td>\n",
-       "      <td>0.370288</td>\n",
-       "      <td>0.327771</td>\n",
-       "      <td>0.464365</td>\n",
-       "      <td>0.347709</td>\n",
-       "      <td>0.319948</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.585344</td>\n",
-       "      <td>0.494285</td>\n",
-       "      <td>0.566579</td>\n",
-       "      <td>0.555662</td>\n",
-       "      <td>0.544435</td>\n",
-       "      <td>0.244654</td>\n",
-       "      <td>0.575187</td>\n",
-       "      <td>0.422255</td>\n",
-       "      <td>0.585876</td>\n",
-       "      <td>0.464987</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>43906</th>\n",
-       "      <td>0.350638</td>\n",
-       "      <td>0.548779</td>\n",
-       "      <td>0.554297</td>\n",
-       "      <td>0.404750</td>\n",
-       "      <td>0.134141</td>\n",
-       "      <td>0.284098</td>\n",
-       "      <td>0.361868</td>\n",
-       "      <td>0.465428</td>\n",
-       "      <td>0.241016</td>\n",
-       "      <td>0.199843</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.561277</td>\n",
-       "      <td>0.542575</td>\n",
-       "      <td>0.601334</td>\n",
-       "      <td>0.563842</td>\n",
-       "      <td>0.556132</td>\n",
-       "      <td>0.289604</td>\n",
-       "      <td>0.564673</td>\n",
-       "      <td>0.448091</td>\n",
-       "      <td>0.589267</td>\n",
-       "      <td>0.497985</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>43907 rows × 120 columns</p>\n",
-       "</div>"
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-       "           Att1      Att2      Att3      Att4      Att5      Att6      Att7  \\\n",
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-       "1      0.508613  0.505837  0.437155  0.490723  0.262201  0.459610  0.393838   \n",
-       "2      0.449571  0.460490  0.453469  0.410779  0.231759  0.402147  0.349590   \n",
-       "3      0.416800  0.548996  0.520850  0.465410  0.181603  0.357255  0.389347   \n",
-       "4      0.501986  0.480820  0.435543  0.432002  0.250599  0.408353  0.357816   \n",
-       "...         ...       ...       ...       ...       ...       ...       ...   \n",
-       "43902  0.426864  0.528629  0.532957  0.401551  0.187178  0.328457  0.363949   \n",
-       "43903  0.344094  0.537319  0.516101  0.430633  0.147998  0.310974  0.373041   \n",
-       "43904  0.329709  0.453422  0.523771  0.314048  0.133553  0.249196  0.296952   \n",
-       "43905  0.470031  0.489588  0.488227  0.356816  0.228900  0.370288  0.327771   \n",
-       "43906  0.350638  0.548779  0.554297  0.404750  0.134141  0.284098  0.361868   \n",
-       "\n",
-       "           Att8      Att9     Att10  ...    Att111    Att112    Att113  \\\n",
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-       "4      0.499186  0.353172  0.327622  ...  0.607607  0.543372  0.566417   \n",
-       "...         ...       ...       ...  ...       ...       ...       ...   \n",
-       "43902  0.487699  0.306376  0.266459  ...  0.610354  0.544168  0.553511   \n",
-       "43903  0.493417  0.249852  0.191468  ...  0.582064  0.527097  0.581796   \n",
-       "43904  0.440839  0.222037  0.196553  ...  0.574960  0.522756  0.594364   \n",
-       "43905  0.464365  0.347709  0.319948  ...  0.585344  0.494285  0.566579   \n",
-       "43906  0.465428  0.241016  0.199843  ...  0.561277  0.542575  0.601334   \n",
-       "\n",
-       "         Att114    Att115    Att116    Att117    Att118    Att119    Att120  \n",
-       "0      0.511032  0.463997  0.202034  0.492341  0.317983  0.547807  0.393778  \n",
-       "1      0.552479  0.511739  0.218366  0.547476  0.348174  0.584991  0.422205  \n",
-       "2      0.496368  0.480986  0.199592  0.535078  0.323834  0.571487  0.397564  \n",
-       "3      0.565105  0.497706  0.252656  0.546756  0.346506  0.589601  0.430145  \n",
-       "4      0.526322  0.484486  0.186909  0.564721  0.325957  0.578370  0.398771  \n",
-       "...         ...       ...       ...       ...       ...       ...       ...  \n",
-       "43902  0.580699  0.559847  0.348502  0.587482  0.488400  0.624835  0.527380  \n",
-       "43903  0.555630  0.515736  0.271329  0.520354  0.410659  0.564902  0.453231  \n",
-       "43904  0.567564  0.524449  0.232201  0.554800  0.408484  0.570778  0.453345  \n",
-       "43905  0.555662  0.544435  0.244654  0.575187  0.422255  0.585876  0.464987  \n",
-       "43906  0.563842  0.556132  0.289604  0.564673  0.448091  0.589267  0.497985  \n",
-       "\n",
-       "[43907 rows x 120 columns]"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.iloc[:, 0: 120]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [
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-       "      <th>43902</th>\n",
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-       "    <tr>\n",
-       "      <th>43903</th>\n",
-       "      <td>0</td>\n",
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-       "      <th>43904</th>\n",
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-       "    <tr>\n",
-       "      <th>43905</th>\n",
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-       "    <tr>\n",
-       "      <th>43906</th>\n",
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-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>43907 rows × 101 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       Class1  Class2  Class3  Class4  Class5  Class6  Class7  Class8  Class9  \\\n",
-       "0           0       0       0       0       0       0       0       0       0   \n",
-       "1           0       0       0       0       0       0       0       0       0   \n",
-       "2           0       0       0       0       0       0       0       0       0   \n",
-       "3           0       0       0       0       0       0       0       0       0   \n",
-       "4           0       0       0       0       0       0       0       0       0   \n",
-       "...       ...     ...     ...     ...     ...     ...     ...     ...     ...   \n",
-       "43902       0       0       0       0       0       0       0       0       0   \n",
-       "43903       0       0       0       0       0       0       0       0       0   \n",
-       "43904       0       0       0       0       0       0       0       0       0   \n",
-       "43905       0       0       0       0       0       0       0       0       0   \n",
-       "43906       0       0       0       0       0       0       0       0       0   \n",
-       "\n",
-       "       Class10  ...  Class92  Class93  Class94  Class95  Class96  Class97  \\\n",
-       "0            0  ...        0        0        0        0        0        0   \n",
-       "1            0  ...        0        0        0        0        0        0   \n",
-       "2            0  ...        0        0        0        0        0        0   \n",
-       "3            0  ...        0        0        0        0        0        0   \n",
-       "4            0  ...        0        0        0        0        0        0   \n",
-       "...        ...  ...      ...      ...      ...      ...      ...      ...   \n",
-       "43902        0  ...        0        0        0        0        1        0   \n",
-       "43903        0  ...        0        0        0        0        1        0   \n",
-       "43904        0  ...        0        0        0        0        1        0   \n",
-       "43905        0  ...        0        0        0        0        0        0   \n",
-       "43906        0  ...        0        0        0        0        1        0   \n",
-       "\n",
-       "       Class98  Class99  Class100  Class101  \n",
-       "0            0        0         0         0  \n",
-       "1            0        0         0         0  \n",
-       "2            0        0         0         0  \n",
-       "3            0        0         0         0  \n",
-       "4            0        0         0         0  \n",
-       "...        ...      ...       ...       ...  \n",
-       "43902        0        0         0         0  \n",
-       "43903        0        0         0         0  \n",
-       "43904        0        0         0         0  \n",
-       "43905        0        0         0         0  \n",
-       "43906        0        0         0         0  \n",
-       "\n",
-       "[43907 rows x 101 columns]"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.iloc[:, 120: 221]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import torch\n",
-    "A = torch.tensor(df.iloc[:, 0: 120].to_numpy()).T\n",
-    "B = torch.tensor(df.iloc[:, 120: 221].to_numpy()).T\n",
-    "B = B.to(torch.float64)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# # save to tensor that C++ can load directly\n",
-    "\n",
-    "from torch import nn\n",
-    "class TensorContainer(nn.Module):\n",
-    "    def __init__(self, tensor_dict):\n",
-    "        super().__init__()\n",
-    "        for key,value in tensor_dict.items():\n",
-    "            setattr(self, key, value)\n",
-    "\n",
-    "tensor_dict = {\n",
-    "    \"A\": A,\n",
-    "    \"B\": B\n",
-    "}\n",
-    "tensors = TensorContainer(tensor_dict)\n",
-    "tensors = torch.jit.script(tensors)\n",
-    "tensors.save('mediamill.pth')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.12"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/benchmark/datasets/Mock.txt b/benchmark/datasets/Mock.txt
deleted file mode 100644
index 94bb605e..00000000
--- a/benchmark/datasets/Mock.txt
+++ /dev/null
@@ -1,150 +0,0 @@
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-54 5.5 2.3 4 1.3 1
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-65 5.6 2.9 3.6 1.3 1
-66 6.7 3.1 4.4 1.4 1
-67 5.6 3 4.5 1.5 1
-68 5.8 2.7 4.1 1 1
-69 6.2 2.2 4.5 1.5 1
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-72 6.1 2.8 4 1.3 1
-73 6.3 2.5 4.9 1.5 1
-74 6.1 2.8 4.7 1.2 1
-75 6.4 2.9 4.3 1.3 1
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-78 6.7 3 5 1.7 1
-79 6 2.9 4.5 1.5 1
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-83 5.8 2.7 3.9 1.2 1
-84 6 2.7 5.1 1.6 1
-85 5.4 3 4.5 1.5 1
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-89 5.6 3 4.1 1.3 1
-90 5.5 2.5 4 1.3 1
-91 5.5 2.6 4.4 1.2 1
-92 6.1 3 4.6 1.4 1
-93 5.8 2.6 4 1.2 1
-94 5 2.3 3.3 1 1
-95 5.6 2.7 4.2 1.3 1
-96 5.7 3 4.2 1.2 1
-97 5.7 2.9 4.2 1.3 1
-98 6.2 2.9 4.3 1.3 1
-99 5.1 2.5 3 1.1 1
-100 5.7 2.8 4.1 1.3 1
-101 6.3 3.3 6 2.5 2
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-105 6.5 3 5.8 2.2 2
-106 7.6 3 6.6 2.1 2
-107 4.9 2.5 4.5 1.7 2
-108 7.3 2.9 6.3 1.8 2
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-110 7.2 3.6 6.1 2.5 2
-111 6.5 3.2 5.1 2 2
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-113 6.8 3 5.5 2.1 2
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-115 5.8 2.8 5.1 2.4 2
-116 6.4 3.2 5.3 2.3 2
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-123 7.7 2.8 6.7 2 2
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-125 6.7 3.3 5.7 2.1 2
-126 7.2 3.2 6 1.8 2
-127 6.2 2.8 4.8 1.8 2
-128 6.1 3 4.9 1.8 2
-129 6.4 2.8 5.6 2.1 2
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-131 7.4 2.8 6.1 1.9 2
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-134 6.3 2.8 5.1 1.5 2
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-137 6.3 3.4 5.6 2.4 2
-138 6.4 3.1 5.5 1.8 2
-139 6 3 4.8 1.8 2
-140 6.9 3.1 5.4 2.1 2
-141 6.7 3.1 5.6 2.4 2
-142 6.9 3.1 5.1 2.3 2
-143 5.8 2.7 5.1 1.9 2
-144 6.8 3.2 5.9 2.3 2
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diff --git a/benchmark/datasets/QCD/README.md b/benchmark/datasets/QCD/README.md
deleted file mode 100644
index 4bc4eda1..00000000
--- a/benchmark/datasets/QCD/README.md
+++ /dev/null
@@ -1,26 +0,0 @@
-QCD: Quantum pHYSICS
-## Background. 
-Lattice gauge theory is a discretization of quantum chromodynamics which is generally accepted to be the fundamental physical theory of strong interactions among the quarks as constituents of matter. The most time-consuming part of a numerical simulation in lattice gauge theory with Wilson fermions on the lattice is the computation of quark propagators within a chromodynamic background gauge field. These computations use up a major part of the world's high performance computing power.
-
-Quark propagators are obtained by solving the inhomogeneous lattice Dirac equation Ax = b, where A = I - kD with 0 <= k < kc is a large but sparse complex non-Hermitian matrix representing a periodic nearest-neighbour coupling on a four-dimensional Euclidean space-time lattice.
-
-From the physical theory it is clear that the matrix A should be positive real (all eigenvalues lie in the right half plane) for 0 <= k < kc. Here, kc represents a critical parameter which depends on the given matrix D. Denoting
-
-\gamma_5 = \left( \begin{array}{cccc}0 & 0 & 1 & 0 \\0 & 0 & 0 & 1 \\1 & 0 & 0 & 0 \\0 & 1 & 0 & 0 \end{array}\right)
-the Wilson fermion matrix A is Gamma-5 symmetric,
-\Gamma_5 A = A^H \Gamma_5,\;\;\;\;\Gamma_5 = I \otimes ( \gamma_5 \otimes I_3 )
-Due to the nearest neighbour coupling, the matrix A has 'property A'. This means that with a red-black (or odd-even) ordering of the grid points the matrix becomes
-
-A = I - kD
-with
-D = \left( \begin{array}{cc}0 & D_{\rm oe}  \\D_{\rm eo} & 0  \end{array}\right)
-
-
-**Note** We have pre-processed the complex matrixies into their modulus:
-- conf5.0-00l4x4-1000 : qcda_small
-- conf5.0-00l4x4-2600 : qcdb_small
-- conf5.4-00l8x8-2000 : qcda_large
-- conf6.0-00l8x8-2000 : qcdb_large
-https://math.nist.gov/MatrixMarket/data/misc/qcd/qcd.html
-
-
diff --git a/benchmark/datasets/QCD/complex_to_modulus.m b/benchmark/datasets/QCD/complex_to_modulus.m
deleted file mode 100644
index d8013236..00000000
--- a/benchmark/datasets/QCD/complex_to_modulus.m
+++ /dev/null
@@ -1,96 +0,0 @@
-## Copyright (C) 2023 tony
-##
-## This program is free software: you can redistribute it and/or modify
-## it under the terms of the GNU General Public License as published by
-## the Free Software Foundation, either version 3 of the License, or
-## (at your option) any later version.
-##
-## This program is distributed in the hope that it will be useful,
-## but WITHOUT ANY WARRANTY; without even the implied warranty of
-## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-## GNU General Public License for more details.
-##
-## You should have received a copy of the GNU General Public License
-## along with this program.  If not, see <https://www.gnu.org/licenses/>.
-
-## -*- texinfo -*-
-## @deftypefn {} {@var{retval} =} complex_to_modulus (@var{input1}, @var{input2})
-##
-## @seealso{}
-## @end deftypefn
-
-## Author: tony <tony@MOSS>
-## Created: 2023-07-29
-
-
-function [complex_matrix,modulus_matrix]=complex_to_modulus(input_file, output_file)
-    % Task 1: Load the complex matrix from .mtx file manually
-    if ~exist(input_file, 'file')
-        error('Input file not found.');
-    end
-    
-    fileID = fopen(input_file, 'r');
-    if fileID == -1
-        error('Error opening input file.');
-    end
-    
-    % Read the header to get matrix size and number of non-zero entries
-    header = fgetl(fileID);
-    if ~strncmp(header, '%%MatrixMarket matrix coordinate complex general', 52)
-        fclose(fileID);
-        error('Invalid Matrix Market format or not a complex matrix.');
-    end
-    
-    % Skip comments (if any)
-    line = fgetl(fileID);
-    while strncmp(line, '%', 1)
-        line = fgetl(fileID);
-    end
-
-    % Read matrix size and number of non-zero entries
-    size_info = sscanf(line, '%d %d %d');
-    m = size_info(1);
-    n = size_info(2);
-    nnz_count = size_info(3);
-    
-    % Read data (non-zero entries) using a loop
-    I = zeros(nnz_count, 1);
-    J = zeros(nnz_count, 1);
-    V = zeros(nnz_count, 1);
-    for k = 1:nnz_count
-        data = sscanf(fgetl(fileID), '%d %d %e');
-        I(k) = data(1) ;  % Adjust for one-based indexing
-        J(k) = data(2) ;  % Adjust for one-based indexing
-        V(k) = data(3);
-    end
-    fclose(fileID);
-
-    % Create complex matrix from data
-    complex_matrix = sparse(I, J, V, m, n);
-
-    % Task 2: Compute the modulus (magnitude) of the complex matrix
-    modulus_matrix = abs(complex_matrix);
-
-    % Task 3: Store the real matrix to disk in .mtx format
-    [I, J, V] = find(modulus_matrix);  % Find non-zero entries
-
-    % Open the output file for writing
-    file = fopen(output_file, 'w');
-    if file == -1
-        error('Error opening output file.');
-    end
-
-    % Write header
-    %fprintf(file,'%');
-    fprintf(file, '%%%%MatrixMarket matrix coordinate real general\n');
-    fprintf(file, '%d %d %d\n', m, n, numel(V));
-
-    % Write data (non-zero entries)
-    for k = 1:numel(V)
-        fprintf(file, '%d %d %.16e\n', I(k), J(k), V(k));
-    end
-
-    % Close the output file
-    fclose(file);
-end
-
diff --git a/benchmark/datasets/QCD/qcda_small.mtx b/benchmark/datasets/QCD/qcda_small.mtx
deleted file mode 100644
index f490d85d..00000000
--- a/benchmark/datasets/QCD/qcda_small.mtx
+++ /dev/null
@@ -1,119810 +0,0 @@
-%%MatrixMarket matrix coordinate real general
-3072 3072 119808
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diff --git a/benchmark/datasets/QCD/qcdb_small.mtx b/benchmark/datasets/QCD/qcdb_small.mtx
deleted file mode 100644
index ae8d132b..00000000
--- a/benchmark/datasets/QCD/qcdb_small.mtx
+++ /dev/null
@@ -1,119810 +0,0 @@
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diff --git a/benchmark/datasets/RDB/README.md b/benchmark/datasets/RDB/README.md
deleted file mode 100644
index 02c35e45..00000000
--- a/benchmark/datasets/RDB/README.md
+++ /dev/null
@@ -1,4 +0,0 @@
-RDB2048: Reaction-diffusion Brusselator Model (Chemical Engineering data)
-for u and epsilon (0,1) cross (0,1) with homogeneous Dirichlet boundary conditions form a 2D reaction-diffusion model where u and v represent the concentrations of two reactions. The equations are discretized with central differences with grid size hu = hv = 1/(n+1) with n=(N/2)^(1/2). For x^T=[u_{1,1}, v_{1,1},u_{1,2},v_{1,2},...,u_{n,n},v_{n,n}, the discretized equations can be written as x dot = f(x). One wants to compute the rightmost eigenvalues of the Jacobi matrix A=df/dx, with the parameters B = 5.45, C = 2, Du = 0.004, Dv = 0.008. The parameter L varies.
-https://math.nist.gov/MatrixMarket/data/NEP/brussel/brussel.html
-
diff --git a/benchmark/datasets/RDB/rdb2048.mtx b/benchmark/datasets/RDB/rdb2048.mtx
deleted file mode 100644
index 1dcde27e..00000000
--- a/benchmark/datasets/RDB/rdb2048.mtx
+++ /dev/null
@@ -1,12034 +0,0 @@
-%%MatrixMarket matrix coordinate real general
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diff --git a/benchmark/datasets/RDB/rdb2048l.mtx b/benchmark/datasets/RDB/rdb2048l.mtx
deleted file mode 100644
index c0466091..00000000
--- a/benchmark/datasets/RDB/rdb2048l.mtx
+++ /dev/null
@@ -1,12034 +0,0 @@
-%%MatrixMarket matrix coordinate real general
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-2045 1981  4.356
-1918 1982  8.712
-1980 1982  8.712
-1981 1982  4
-1982 1982 -38.848
-1984 1982  8.712
-2046 1982  8.712
-1919 1983  4.356
-1981 1983  4.356
-1983 1983 -12.974
-1984 1983 -5.45
-2047 1983  4.356
-1920 1984  8.712
-1982 1984  8.712
-1983 1984  4
-1984 1984 -38.848
-2048 1984  8.712
-1921 1985  4.356
-1985 1985 -12.974
-1986 1985 -5.45
-1987 1985  4.356
-1922 1986  8.712
-1985 1986  4
-1986 1986 -38.848
-1988 1986  8.712
-1923 1987  4.356
-1985 1987  4.356
-1987 1987 -12.974
-1988 1987 -5.45
-1989 1987  4.356
-1924 1988  8.712
-1986 1988  8.712
-1987 1988  4
-1988 1988 -38.848
-1990 1988  8.712
-1925 1989  4.356
-1987 1989  4.356
-1989 1989 -12.974
-1990 1989 -5.45
-1991 1989  4.356
-1926 1990  8.712
-1988 1990  8.712
-1989 1990  4
-1990 1990 -38.848
-1992 1990  8.712
-1927 1991  4.356
-1989 1991  4.356
-1991 1991 -12.974
-1992 1991 -5.45
-1993 1991  4.356
-1928 1992  8.712
-1990 1992  8.712
-1991 1992  4
-1992 1992 -38.848
-1994 1992  8.712
-1929 1993  4.356
-1991 1993  4.356
-1993 1993 -12.974
-1994 1993 -5.45
-1995 1993  4.356
-1930 1994  8.712
-1992 1994  8.712
-1993 1994  4
-1994 1994 -38.848
-1996 1994  8.712
-1931 1995  4.356
-1993 1995  4.356
-1995 1995 -12.974
-1996 1995 -5.45
-1997 1995  4.356
-1932 1996  8.712
-1994 1996  8.712
-1995 1996  4
-1996 1996 -38.848
-1998 1996  8.712
-1933 1997  4.356
-1995 1997  4.356
-1997 1997 -12.974
-1998 1997 -5.45
-1999 1997  4.356
-1934 1998  8.712
-1996 1998  8.712
-1997 1998  4
-1998 1998 -38.848
-2000 1998  8.712
-1935 1999  4.356
-1997 1999  4.356
-1999 1999 -12.974
-2000 1999 -5.45
-2001 1999  4.356
-1936 2000  8.712
-1998 2000  8.712
-1999 2000  4
-2000 2000 -38.848
-2002 2000  8.712
-1937 2001  4.356
-1999 2001  4.356
-2001 2001 -12.974
-2002 2001 -5.45
-2003 2001  4.356
-1938 2002  8.712
-2000 2002  8.712
-2001 2002  4
-2002 2002 -38.848
-2004 2002  8.712
-1939 2003  4.356
-2001 2003  4.356
-2003 2003 -12.974
-2004 2003 -5.45
-2005 2003  4.356
-1940 2004  8.712
-2002 2004  8.712
-2003 2004  4
-2004 2004 -38.848
-2006 2004  8.712
-1941 2005  4.356
-2003 2005  4.356
-2005 2005 -12.974
-2006 2005 -5.45
-2007 2005  4.356
-1942 2006  8.712
-2004 2006  8.712
-2005 2006  4
-2006 2006 -38.848
-2008 2006  8.712
-1943 2007  4.356
-2005 2007  4.356
-2007 2007 -12.974
-2008 2007 -5.45
-2009 2007  4.356
-1944 2008  8.712
-2006 2008  8.712
-2007 2008  4
-2008 2008 -38.848
-2010 2008  8.712
-1945 2009  4.356
-2007 2009  4.356
-2009 2009 -12.974
-2010 2009 -5.45
-2011 2009  4.356
-1946 2010  8.712
-2008 2010  8.712
-2009 2010  4
-2010 2010 -38.848
-2012 2010  8.712
-1947 2011  4.356
-2009 2011  4.356
-2011 2011 -12.974
-2012 2011 -5.45
-2013 2011  4.356
-1948 2012  8.712
-2010 2012  8.712
-2011 2012  4
-2012 2012 -38.848
-2014 2012  8.712
-1949 2013  4.356
-2011 2013  4.356
-2013 2013 -12.974
-2014 2013 -5.45
-2015 2013  4.356
-1950 2014  8.712
-2012 2014  8.712
-2013 2014  4
-2014 2014 -38.848
-2016 2014  8.712
-1951 2015  4.356
-2013 2015  4.356
-2015 2015 -12.974
-2016 2015 -5.45
-2017 2015  4.356
-1952 2016  8.712
-2014 2016  8.712
-2015 2016  4
-2016 2016 -38.848
-2018 2016  8.712
-1953 2017  4.356
-2015 2017  4.356
-2017 2017 -12.974
-2018 2017 -5.45
-2019 2017  4.356
-1954 2018  8.712
-2016 2018  8.712
-2017 2018  4
-2018 2018 -38.848
-2020 2018  8.712
-1955 2019  4.356
-2017 2019  4.356
-2019 2019 -12.974
-2020 2019 -5.45
-2021 2019  4.356
-1956 2020  8.712
-2018 2020  8.712
-2019 2020  4
-2020 2020 -38.848
-2022 2020  8.712
-1957 2021  4.356
-2019 2021  4.356
-2021 2021 -12.974
-2022 2021 -5.45
-2023 2021  4.356
-1958 2022  8.712
-2020 2022  8.712
-2021 2022  4
-2022 2022 -38.848
-2024 2022  8.712
-1959 2023  4.356
-2021 2023  4.356
-2023 2023 -12.974
-2024 2023 -5.45
-2025 2023  4.356
-1960 2024  8.712
-2022 2024  8.712
-2023 2024  4
-2024 2024 -38.848
-2026 2024  8.712
-1961 2025  4.356
-2023 2025  4.356
-2025 2025 -12.974
-2026 2025 -5.45
-2027 2025  4.356
-1962 2026  8.712
-2024 2026  8.712
-2025 2026  4
-2026 2026 -38.848
-2028 2026  8.712
-1963 2027  4.356
-2025 2027  4.356
-2027 2027 -12.974
-2028 2027 -5.45
-2029 2027  4.356
-1964 2028  8.712
-2026 2028  8.712
-2027 2028  4
-2028 2028 -38.848
-2030 2028  8.712
-1965 2029  4.356
-2027 2029  4.356
-2029 2029 -12.974
-2030 2029 -5.45
-2031 2029  4.356
-1966 2030  8.712
-2028 2030  8.712
-2029 2030  4
-2030 2030 -38.848
-2032 2030  8.712
-1967 2031  4.356
-2029 2031  4.356
-2031 2031 -12.974
-2032 2031 -5.45
-2033 2031  4.356
-1968 2032  8.712
-2030 2032  8.712
-2031 2032  4
-2032 2032 -38.848
-2034 2032  8.712
-1969 2033  4.356
-2031 2033  4.356
-2033 2033 -12.974
-2034 2033 -5.45
-2035 2033  4.356
-1970 2034  8.712
-2032 2034  8.712
-2033 2034  4
-2034 2034 -38.848
-2036 2034  8.712
-1971 2035  4.356
-2033 2035  4.356
-2035 2035 -12.974
-2036 2035 -5.45
-2037 2035  4.356
-1972 2036  8.712
-2034 2036  8.712
-2035 2036  4
-2036 2036 -38.848
-2038 2036  8.712
-1973 2037  4.356
-2035 2037  4.356
-2037 2037 -12.974
-2038 2037 -5.45
-2039 2037  4.356
-1974 2038  8.712
-2036 2038  8.712
-2037 2038  4
-2038 2038 -38.848
-2040 2038  8.712
-1975 2039  4.356
-2037 2039  4.356
-2039 2039 -12.974
-2040 2039 -5.45
-2041 2039  4.356
-1976 2040  8.712
-2038 2040  8.712
-2039 2040  4
-2040 2040 -38.848
-2042 2040  8.712
-1977 2041  4.356
-2039 2041  4.356
-2041 2041 -12.974
-2042 2041 -5.45
-2043 2041  4.356
-1978 2042  8.712
-2040 2042  8.712
-2041 2042  4
-2042 2042 -38.848
-2044 2042  8.712
-1979 2043  4.356
-2041 2043  4.356
-2043 2043 -12.974
-2044 2043 -5.45
-2045 2043  4.356
-1980 2044  8.712
-2042 2044  8.712
-2043 2044  4
-2044 2044 -38.848
-2046 2044  8.712
-1981 2045  4.356
-2043 2045  4.356
-2045 2045 -12.974
-2046 2045 -5.45
-2047 2045  4.356
-1982 2046  8.712
-2044 2046  8.712
-2045 2046  4
-2046 2046 -38.848
-2048 2046  8.712
-1983 2047  4.356
-2045 2047  4.356
-2047 2047 -12.974
-2048 2047 -5.45
-1984 2048  8.712
-2046 2048  8.712
-2047 2048  4
-2048 2048 -38.848
diff --git a/benchmark/datasets/README.md b/benchmark/datasets/README.md
index 7d09c9fc..0fe56869 100644
--- a/benchmark/datasets/README.md
+++ b/benchmark/datasets/README.md
@@ -1,24 +1,65 @@
-# The real world datasets
-This folder contains all real-world datasets
-## Stand-alone MM/AMM datasets
-They are used for computing the similarity of two matrixes or the covariance of one matrix
-, by matmul(A,B.t()) or matmul(A,A.t()).
-   | Dataset Name | Application Filed  | Size for A,B | If Streaming     |
-   | -------------|--------------------|--------------|------------------|
-   | AST          | Astrophysics       | 765*765      | 2 stream         |
-   | BUS          | Land Traffic       | 4929*10595   | 2 stream         |
-   | DWAVE        | Integrated Circuit | 512*512      | 1 stream+1 Static |
-   | ECO          | Economic Models    | 207*260      | 1 stream+1 Static |
-   | QCD(Large)   | Quantum Physics    | 49152*49152  | 2 stream         |
-   | QCD(Small)   | Quantum Physics    | 3072*3072    | 2 stream         |
-   | RDB          | Chemical Engineer  | 2048*2048    | 2 stream         |
-   | UTM          | Plasma Physics     | 1700*1700    | 2 stream         |
-   | ZENOIS       | Air Traffic        | 2873*2873    | 1 stream+1 Static |
-
-## Note 
-We have moved the QCD(Large) outside due to size restrictions,
-Please use this link:xxxxx
-
-   
+# LibAMM Benchmark Datasets - MOVED
 
+⚠️ **The benchmark datasets have been moved to a centralized location.**
 
+## New Location
+
+The LibAMM benchmark datasets are now hosted in the **sageData** repository for centralized management:
+
+📦 **Repository**: https://github.com/intellistream/sageData
+
+📁 **Path**: `libamm-benchmark/datasets/`
+
+## Why the Move?
+
+- **Centralized Management**: Share datasets across multiple SAGE ecosystem projects
+- **Reduced Repository Size**: LibAMM repo is now ~325MB lighter
+- **Git LFS Support**: Large binary files are efficiently managed
+- **Better Organization**: Datasets grouped by type/domain
+
+## How to Use Datasets
+
+### Option 1: Skip Dataset Copy (Default for embedded usage)
+
+When using LibAMM as a library (e.g., in sageDB), datasets are not needed:
+
+```cmake
+set(LIBAMM_SKIP_DATASET_COPY ON CACHE BOOL "Skip dataset copy" FORCE)
+```
+
+### Option 2: Use Centralized Datasets from sageData
+
+If you need to run LibAMM benchmarks:
+
+1. Clone sageData repository:
+   ```bash
+   git clone https://github.com/intellistream/sageData.git
+   cd sageData
+   git lfs install
+   git lfs pull  # Download LFS files
+   ```
+
+2. Point LibAMM to the datasets:
+   ```cmake
+   set(LIBAMM_SKIP_DATASET_COPY OFF)
+   set(LIBAMM_DATASET_SOURCE_DIR "/path/to/sageData/libamm-benchmark/datasets")
+   ```
+
+### Option 3: Download Manually
+
+You can also download specific datasets you need from the sageData repository.
+
+## Available Datasets
+
+See [sageData/libamm-benchmark/README.md](https://github.com/intellistream/sageData/tree/main/libamm-benchmark) for:
+- Complete dataset list
+- Size and domain information  
+- Usage instructions
+
+## Migration Date
+
+Datasets migrated: November 2025
+
+## Questions?
+
+For dataset-related issues, please open an issue in the sageData repository.
diff --git a/benchmark/datasets/SIFT/README.md b/benchmark/datasets/SIFT/README.md
deleted file mode 100644
index df31a310..00000000
--- a/benchmark/datasets/SIFT/README.md
+++ /dev/null
@@ -1 +0,0 @@
-http://corpus-texmex.irisa.fr/
\ No newline at end of file
diff --git a/benchmark/datasets/SIFT/siftsmall_base.fvecs b/benchmark/datasets/SIFT/siftsmall_base.fvecs
deleted file mode 100644
index e3b90ae1..00000000
Binary files a/benchmark/datasets/SIFT/siftsmall_base.fvecs and /dev/null differ
diff --git a/benchmark/datasets/UTM/README.md b/benchmark/datasets/UTM/README.md
deleted file mode 100644
index 4c417865..00000000
--- a/benchmark/datasets/UTM/README.md
+++ /dev/null
@@ -1,4 +0,0 @@
-UTM1700: Tokamak Matrices (plasma physics)
-Describing two tokamak models
-https://math.nist.gov/MatrixMarket/data/SPARSKIT/tokamak/utm1700b.html
-
diff --git a/benchmark/datasets/UTM/utm1700a.mtx b/benchmark/datasets/UTM/utm1700a.mtx
deleted file mode 100644
index e32dcd9a..00000000
--- a/benchmark/datasets/UTM/utm1700a.mtx
+++ /dev/null
@@ -1,21315 +0,0 @@
-%%MatrixMarket matrix coordinate real general
-1700 1700 21313
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diff --git a/benchmark/datasets/UTM/utm1700b.mtx b/benchmark/datasets/UTM/utm1700b.mtx
deleted file mode 100644
index 5f86a504..00000000
--- a/benchmark/datasets/UTM/utm1700b.mtx
+++ /dev/null
@@ -1,21511 +0,0 @@
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diff --git a/benchmark/datasets/ZENIOS/README.md b/benchmark/datasets/ZENIOS/README.md
deleted file mode 100644
index 4289b793..00000000
--- a/benchmark/datasets/ZENIOS/README.md
+++ /dev/null
@@ -1,4 +0,0 @@
-ZENIOS: Air-traffic Control Model.
-This matrix is the Hessian of the objective function. Several rows will be zero corresponding to variables not in the basis at the time the matrix was generated. Zenios solved a projection of the Hessian using conjugate gradient algorithms.
-https://math.nist.gov/MatrixMarket/data/Harwell-Boeing/airtfc/zenios.html
-
diff --git a/benchmark/datasets/ZENIOS/zenios.mtx b/benchmark/datasets/ZENIOS/zenios.mtx
deleted file mode 100644
index 263a92b5..00000000
--- a/benchmark/datasets/ZENIOS/zenios.mtx
+++ /dev/null
@@ -1,15034 +0,0 @@
-%%MatrixMarket matrix coordinate real symmetric
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