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REF: Update experiment configuration JSONs (#29)
* STY: Normalize formatting in experiment config files * REF: Fix dataset paths and update dataset list * REF: Rename SVMOP config file * FIX: Correct classifier names, config keys and cv_metric in config JSONs * MNT: Remove obsolote experiment config * REF: Update classifier parameters and hyperparameters * REF: Update configuration names * REF: Update classifier paths
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11 files changed

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‎orca_python/configurations/full_functionality_test.json‎

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{
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"general_conf": {
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"basedir": "orca_python/datasets/data",
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"datasets": ["tae", "balance-scale", "contact-lenses"],
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"hyperparam_cv_nfolds": 3,
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"jobs": 10,
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"input_preprocessing": "std",
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"output_folder": "my_runs/",
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"metrics": ["ccr", "mae", "amae", "mze"],
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"cv_metric": "mae"
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},
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"configurations": {
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"SVM": {
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"classifier": "sklearn.svm.SVC",
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"parameters": {
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"C": [0.001, 0.1, 1, 10, 100],
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"gamma": [0.1, 1, 10]
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}
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},
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"SVMOP": {
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"classifier": "orca_python.classifiers.OrdinalDecomposition",
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"parameters": {
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"dtype": "ordered_partitions",
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"decision_method": "frank_hall",
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"base_classifier": "sklearn.svm.SVC",
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"parameters": {
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"C": [0.01, 0.1, 1, 10],
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"gamma": [0.01, 0.1, 1, 10],
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"probability": ["True"]
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}
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}
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},
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"LR": {
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"classifier": "orca_python.classifiers.OrdinalDecomposition",
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"parameters": {
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"dtype": ["ordered_partitions", "one_vs_next"],
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"decision_method": "exponential_loss",
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"base_classifier": "sklearn.linear_model.LogisticRegression",
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"parameters": {
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"solver": ["liblinear"],
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"C": [0.01, 0.1, 1, 10],
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"penalty": ["l1","l2"]
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}
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}
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},
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"REDSVM": {
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"classifier": "orca_python.classifiers.REDSVM",
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"parameters": {
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"kernel": 2,
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"degree": 3,
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"gamma": 0.1,
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"coef0": 0,
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"C": 1,
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"tol": 0.001,
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"shrinking": 1
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}
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},
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"SVOREX": {
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"classifier": "orca_python.classifiers.SVOREX",
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"parameters": {
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"kernel": 0,
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"C": [0.1, 1, 10],
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"kappa": [0.1, 1, 10],
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"tol": 0.001
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}
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}
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}
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"general_conf": {
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"basedir": "orca_python/datasets/data",
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"datasets": [
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"balance-scale",
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"car",
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"contact-lenses",
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"ERA",
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"tae",
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"winequality-red"
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],
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"hyperparam_cv_nfolds": 3,
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"jobs": 10,
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"input_preprocessing": "std",
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"output_folder": "my_runs/",
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"metrics": ["ccr", "mae", "amae", "mze"],
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"cv_metric": "mae"
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},
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"configurations": {
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"SVM": {
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"classifier": "sklearn.svm.SVC",
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"parameters": {
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"C": [0.001, 0.1, 1, 10, 100],
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"gamma": [0.1, 1, 10]
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}
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},
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"SVMOP": {
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"classifier": "orca_python.classifiers.OrdinalDecomposition",
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"parameters": {
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"dtype": "ordered_partitions",
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"decision_method": "frank_hall",
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"base_classifier": "sklearn.svm.SVC",
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"parameters": {
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"C": [0.01, 0.1, 1, 10],
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"gamma": [0.01, 0.1, 1, 10],
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"probability": ["True"]
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}
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}
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},
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"LR": {
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"classifier": "orca_python.classifiers.OrdinalDecomposition",
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"parameters": {
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"dtype": ["ordered_partitions", "one_vs_next"],
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"decision_method": "exponential_loss",
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"base_classifier": "sklearn.linear_model.LogisticRegression",
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"parameters": {
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"solver": ["liblinear"],
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"C": [0.01, 0.1, 1, 10],
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"penalty": ["l1", "l2"]
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}
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}
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},
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"REDSVM": {
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"classifier": "orca_python.classifiers.REDSVM",
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"parameters": {
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"kernel": "rbf",
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"degree": 3,
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"gamma": 0.1,
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"coef0": 0,
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"C": 1,
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"tol": 0.001,
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"shrinking": 1
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}
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},
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"SVOREX": {
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"classifier": "orca_python.classifiers.SVOREX",
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"parameters": {
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"kernel": "gaussian",
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"C": [0.1, 1, 10],
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"kappa": [0.1, 1, 10],
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"tol": 0.001
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}
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}
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}
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}

‎orca_python/configurations/nnop_mae_test.json‎

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{
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"general_conf": {
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"basedir": "datasets",
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"datasets": ["balance-scale", "contact-lenses", "tae", "car", "winequality-red", "ERA"],
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"hyperparam_cv_nfolds": 5,
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"jobs": 10,
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"input_preprocessing": "std",
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"output_folder": "my_runs/",
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"metrics": ["ccr", "mae", "mze"],
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"cv_metric": "mae"
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},
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"configurations": {
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"nnop-mae": {
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"classifier": "NNOP",
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"parameters": {
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"basedir": "orca_python/datasets/data",
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"datasets": ["balance-scale"],
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"hyperparam_cv_nfolds": 3,
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"jobs": 10,
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"input_preprocessing": "std",
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"output_folder": "my_runs/",
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"metrics": ["ccr", "mae", "mze"],
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"cv_metric": "mae"
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},
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"configurations": {
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"NNOP-MAE": {
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"classifier": "orca_python.classifiers.NNOP",
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"parameters": {
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"epsilon_init": 0.5,
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"n_hidden": [5,10,20,30,40,50],
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"n_hidden": [5, 10, 20, 30, 40, 50],
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"max_iter": [250, 500],
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"lambda_value": [0, 0.01, 1]
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"lambda_value": [0, 0.01, 1]
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}
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}
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}
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}
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}
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}

‎orca_python/configurations/nnop_mze_test.json‎

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{
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"general_conf": {
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"basedir": "datasets",
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"datasets": ["balance-scale", "contact-lenses", "tae", "car", "winequality-red", "ERA"],
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"hyperparam_cv_nfolds": 5,
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"basedir": "orca_python/datasets/data",
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"datasets": ["balance-scale"],
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"hyperparam_cv_nfolds": 3,
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"jobs": 10,
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"input_preprocessing": "std",
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"output_folder": "my_runs/",
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"metrics": ["ccr", "mae", "mze"],
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"cv_metric": "mze"
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},
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"configurations": {
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"nnop-mze": {
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"classifier": "NNPOM",
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"NNOP-MZE": {
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"classifier": "orca_python.classifiers.NNOP",
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"parameters": {
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"epsilon_init": 0.5,
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"n_hidden": [5,10,20,30,40,50],
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"n_hidden": [5, 10, 20, 30, 40, 50],
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"max_iter": [250, 500],
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"lambda_value": [0, 0.01, 1]
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}
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}
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}
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}

‎orca_python/configurations/nnop_test.json‎

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This file was deleted.

‎orca_python/configurations/nnpom_mae_test.json‎

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{
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"general_conf": {
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"basedir": "tests/test_datasets/test_nnpom_nnop_load_dataset",
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"datasets": ["toy"],
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"hyperparam_cv_nfolds": 5,
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"basedir": "orca_python/datasets/data",
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"datasets": ["balance-scale"],
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"hyperparam_cv_nfolds": 3,
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"jobs": 10,
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"input_preprocessing": "std",
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"output_folder": "my_runs/",
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"metrics": ["ccr", "mae", "mze"],
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"cv_metric": "ccr"
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"cv_metric": "mae"
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},
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"configurations": {
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"expectedPredictions0": {
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"classifier": "NNPOM",
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"NNPOM-MAE": {
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"classifier": "orca_python.classifiers.NNPOM",
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"parameters": {
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"epsilon_init": 0.5,
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"n_hidden": 10,
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"max_iter": 500,
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"lambda_value": 0.01
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"n_hidden": [5, 10, 20, 30, 40, 50],
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"max_iter": [250, 500],
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"lambda_value": [0, 0.01, 1]
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}
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}
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}
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}

‎orca_python/configurations/nnpom_mze_test.json‎

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{
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"general_conf": {
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"basedir": "datasets",
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"datasets": ["balance-scale", "contact-lenses", "tae", "car", "winequality-red", "ERA"],
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"hyperparam_cv_nfolds": 5,
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"jobs": 10,
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"input_preprocessing": "std",
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"output_folder": "my_runs/",
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"metrics": ["ccr", "mae", "mze"],
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"cv_metric": "mze"
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},
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"configurations": {
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"nnop-mze": {
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"classifier": "NNOP",
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"parameters": {
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"basedir": "orca_python/datasets/data",
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"datasets": ["balance-scale"],
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"hyperparam_cv_nfolds": 3,
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"jobs": 10,
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"input_preprocessing": "std",
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"output_folder": "my_runs/",
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"metrics": ["ccr", "mae", "mze"],
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"cv_metric": "mze"
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},
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"configurations": {
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"NNPOM-MZE": {
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"classifier": "orca_python.classifiers.NNPOM",
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"parameters": {
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"epsilon_init": 0.5,
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"n_hidden": [5,10,20,30,40,50],
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"n_hidden": [5, 10, 20, 30, 40, 50],
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"max_iter": [250, 500],
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"lambda_value": [0, 0.01, 1]
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"lambda_value": [0, 0.01, 1]
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}
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}
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}
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}
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}
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}

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