WIP Update to 0.2

Author: folmos-at-orange

CHANGELOG.md

@@ -1,10 +1,17 @@
 # Changelog
 
+## [0.2] - 2025-12-26
+
+### Changed
+- Update Khiops dependency to version 11.
+
 ## [0.1] - 2025-10-17
+
 ### Added
 - `KhalibClassifier` class
 - `calibration_error` function
 - `build_reliability_diagram` function
 
-[Unreleased]: https://github.com/yourusername/yourproject/compare/0.1...HEAD
-[1.0.0]: https://github.com/yourusername/yourproject/releases/tag/0.1
+[Unreleased]: https://github.com/yourusername/yourproject/compare/0.2...HEAD
+[0.2]: https://github.com/yourusername/yourproject/compare/0.1...0.2
+[0.1]: https://github.com/yourusername/yourproject/releases/tag/0.1

README.md

@@ -6,13 +6,16 @@ suite.
 
 ## Features
 - `KhalibClassifier`: A scikit-learn estimator to calibrate classifiers with a similar interface
-  fashion as [CalibratedClassifierCV][sk-calclf].
+  as [CalibratedClassifierCV][sk-calclf].
 - `calibration_error` : A function to estimate the Estimated Calibration Error (ECE).
-- `build_reliability_diagram` : A function that builds a reliability diagram.
+- `build_reliability_diagram` : A function to build a reliability diagram.
 
 These features are based on Khiops's non-parametric supervised histograms, so there is no need to
 specify the number and width of the bins, as they are automatically estimated from data.
 
+[khiops-org]: https://khiops.org
+[sk-calclf]: https://scikit-learn.org/stable/modules/generated/sklearn.calibration.CalibratedClassifierCV.html
+
 <!-- end-summary -->
 
 See the [documentation][khalib-docs] for more information.
@@ -23,9 +26,10 @@ See the [documentation][khalib-docs] for more information.
 - [Install Khiops][khiops-setup]
 - Install the `khalib` python library:
 
-```bash
-pip install https://github.com/KhiopsLab/khalib/archive/refs/tags/0.1.zip
+```sh
+pip install khalib
 ```
+[khiops-setup]: https://khiops.org/setup/
 
 <!-- end-install -->
 
@@ -35,8 +39,4 @@ pip install https://github.com/KhiopsLab/khalib/archive/refs/tags/0.1.zip
 See https://khiopslab.github.io/khalib/
 
 
-[khiops-org]: https://khiops.org
-[khiops11-setup]: https://khiops.org/11.0.0-b.0/setup/
-[sk-calclf]: https://scikit-learn.org/stable/modules/generated/sklearn.calibration.CalibratedClassifierCV.html
 [khalib-docs]: https://khiopslab.github.io/khalib
-

docs/index.md

@@ -11,17 +11,14 @@
 ## How does it work
 
 `khalib` proposes histogram-based calibration and its error estimation. Its differentiating factor
-is that uses [Khiops][khiops-org] to construct the histogram in which {math}`P(Y = 1 | S)` is
-estimated. These histograms have the following properties:
+is that uses Khiops to construct the histogram in which {math}`P(Y = 1 | S)` is estimated. These
+histograms have the following properties:
 - They balance class purity, model complexity and data fitness.
 - They are non-parametric: The optimal histogram is searched without constraint in number of bins or
   bin width. This implies that the user doesn't need to set a number of bins nor their widths.
 
 
-[khiops-org]: https://khiops.org
-[khiops-setup]: https://khiops.org/setup/
-[sk-calclf]: https://scikit-learn.org/stable/modules/generated/sklearn.calibration.CalibratedClassifierCV.html
-[khalib-docs]: https://khiopsml.github.io/khalib
+<!--[khiops-org]: https://khiops.org-->
 
 
 See the [Quickstart](quickstart) and [API reference](api) to learn how to use the library.
@@ -40,5 +37,6 @@ API Reference <api>
 :hidden:
 
 Khiops <https://www.khiops.org>
+Github <https://github.com/KhiopsLab/khalib>
 ```
 

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "khalib"
-version = "0.2rc2"
+version = "0.2"
 description = "Classifier Calibration with Khiops"
 authors = [{ name = "Felipe Olmos", email = "luisfelipe.olmosmarchant@orange.com" }]
 requires-python = ">=3.11"