Run
8885411

Run 8885411

Task 167132 (Supervised Classification) Speech Uploaded 14-03-2018 by Mathyn Scheerder
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Flow

sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.StandardScaler, feat=sklearn.feature_selection.univariate_selection.SelectKBest,clf=sklearn .linear_model.logistic.LogisticRegression)(1)Automatically created scikit-learn flow.
sklearn.preprocessing.data.StandardScaler(5)_copytrue
sklearn.preprocessing.data.StandardScaler(5)_with_meantrue
sklearn.preprocessing.data.StandardScaler(5)_with_stdtrue
sklearn.linear_model.logistic.LogisticRegression(10)_C0.5
sklearn.linear_model.logistic.LogisticRegression(10)_class_weightnull
sklearn.linear_model.logistic.LogisticRegression(10)_dualfalse
sklearn.linear_model.logistic.LogisticRegression(10)_fit_intercepttrue
sklearn.linear_model.logistic.LogisticRegression(10)_intercept_scaling1
sklearn.linear_model.logistic.LogisticRegression(10)_max_iter100
sklearn.linear_model.logistic.LogisticRegression(10)_multi_class"ovr"
sklearn.linear_model.logistic.LogisticRegression(10)_n_jobs-1
sklearn.linear_model.logistic.LogisticRegression(10)_penalty"l1"
sklearn.linear_model.logistic.LogisticRegression(10)_random_state51304
sklearn.linear_model.logistic.LogisticRegression(10)_solver"liblinear"
sklearn.linear_model.logistic.LogisticRegression(10)_tol0.0001
sklearn.linear_model.logistic.LogisticRegression(10)_verbose0
sklearn.linear_model.logistic.LogisticRegression(10)_warm_startfalse
sklearn.feature_selection.univariate_selection.SelectKBest(2)_k100
sklearn.feature_selection.univariate_selection.SelectKBest(2)_score_func{"oml-python:serialized_object": "function", "value": "sklearn.feature_selection.univariate_selection.f_classif"}
sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.StandardScaler,feat=sklearn.feature_selection.univariate_selection.SelectKBest,clf=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

Area under ROC curve
0.8252 ± 0.0961
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9746 ± 0.0034
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0464 ± 0.1059
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-5227.9193 ± 126.7811
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.029 ± 0.0031
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0328 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Number of instances
3686
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9699 ± 0.0068
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9805 ± 0.004
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.1231
Cross-validation details (10-fold Crossvalidation)
Recall
0.9805 ± 0.004
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8828 ± 0.1063
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.1276 ± 0.0031
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1319 ± 0.0091
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0341 ± 0.082
Cross-validation details (10-fold Crossvalidation)