Run
10560595

Run 10560595

Task 9952 (Supervised Classification) phoneme Uploaded 14-08-2021 by Sergey Redyuk
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Flow

sklearn.linear_model.logistic.LogisticRegression(38)Logistic Regression (aka logit, MaxEnt) classifier. In the multiclass case, the training algorithm uses the one-vs-rest (OvR) scheme if the 'multi_class' option is set to 'ovr', and uses the cross- entropy loss if the 'multi_class' option is set to 'multinomial'. (Currently the 'multinomial' option is supported only by the 'lbfgs', 'sag' and 'newton-cg' solvers.) This class implements regularized logistic regression using the 'liblinear' library, 'newton-cg', 'sag' and 'lbfgs' solvers. It can handle both dense and sparse input. Use C-ordered arrays or CSR matrices containing 64-bit floats for optimal performance; any other input format will be converted (and copied). The 'newton-cg', 'sag', and 'lbfgs' solvers support only L2 regularization with primal formulation. The 'liblinear' solver supports both L1 and L2 regularization, with a dual formulation only for the L2 penalty.
sklearn.linear_model.logistic.LogisticRegression(38)_C0.001
sklearn.linear_model.logistic.LogisticRegression(38)_class_weight"balanced"
sklearn.linear_model.logistic.LogisticRegression(38)_dualfalse
sklearn.linear_model.logistic.LogisticRegression(38)_fit_intercepttrue
sklearn.linear_model.logistic.LogisticRegression(38)_intercept_scaling1
sklearn.linear_model.logistic.LogisticRegression(38)_max_iter10000
sklearn.linear_model.logistic.LogisticRegression(38)_multi_class"auto"
` for more details.">sklearn.linear_model.logistic.LogisticRegression(38)_n_jobsnull
sklearn.linear_model.logistic.LogisticRegression(38)_penalty"l2"
sklearn.linear_model.logistic.LogisticRegression(38)_random_state45025
sklearn.linear_model.logistic.LogisticRegression(38)_solver"lbfgs"
sklearn.linear_model.logistic.LogisticRegression(38)_tol0.0001
sklearn.linear_model.logistic.LogisticRegression(38)_verbose0
sklearn.linear_model.logistic.LogisticRegression(38)_warm_startfalse

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.

18 Evaluation measures

0.812 ± 0.0199
Per class
Cross-validation details (10-fold Crossvalidation)
0.7443 ± 0.0203
Per class
Cross-validation details (10-fold Crossvalidation)
0.4348 ± 0.0424
Cross-validation details (10-fold Crossvalidation)
-0.0122 ± 0.0257
Cross-validation details (10-fold Crossvalidation)
0.4077 ± 0.007
Cross-validation details (10-fold Crossvalidation)
0.4147 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.7333 ± 0.0214
Cross-validation details (10-fold Crossvalidation)
5404
Per class
Cross-validation details (10-fold Crossvalidation)
0.7825 ± 0.0197
Per class
Cross-validation details (10-fold Crossvalidation)
0.7333 ± 0.0214
Cross-validation details (10-fold Crossvalidation)
0.8732 ± 0.001
Cross-validation details (10-fold Crossvalidation)
0.983 ± 0.0171
Cross-validation details (10-fold Crossvalidation)
0.4554 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
0.4334 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
0.9519 ± 0.016
Cross-validation details (10-fold Crossvalidation)
0.7473 ± 0.0244
Cross-validation details (10-fold Crossvalidation)