Run
10560094

Run 10560094

Task 167119 (Supervised Classification) jungle_chess_2pcs_raw_endgame_complete Uploaded 13-08-2021 by Sergey Redyuk
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Flow

sklearn.linear_model.logistic.LogisticRegression(35)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(35)_C1.0
sklearn.linear_model.logistic.LogisticRegression(35)_class_weightnull
sklearn.linear_model.logistic.LogisticRegression(35)_dualfalse
sklearn.linear_model.logistic.LogisticRegression(35)_fit_intercepttrue
sklearn.linear_model.logistic.LogisticRegression(35)_intercept_scaling1
sklearn.linear_model.logistic.LogisticRegression(35)_max_iter100
sklearn.linear_model.logistic.LogisticRegression(35)_multi_class"ovr"
sklearn.linear_model.logistic.LogisticRegression(35)_n_jobs1
sklearn.linear_model.logistic.LogisticRegression(35)_penalty"l2"
sklearn.linear_model.logistic.LogisticRegression(35)_random_state13352
sklearn.linear_model.logistic.LogisticRegression(35)_solver"liblinear"
sklearn.linear_model.logistic.LogisticRegression(35)_tol0.0001
sklearn.linear_model.logistic.LogisticRegression(35)_verbose0
sklearn.linear_model.logistic.LogisticRegression(35)_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

0.8073 ± 0.0061
Per class
Cross-validation details (10-fold Crossvalidation)
0.65 ± 0.0063
Per class
Cross-validation details (10-fold Crossvalidation)
0.4066 ± 0.012
Cross-validation details (10-fold Crossvalidation)
0.303 ± 0.0063
Cross-validation details (10-fold Crossvalidation)
0.2876 ± 0.002
Cross-validation details (10-fold Crossvalidation)
0.3832 ± 0
Cross-validation details (10-fold Crossvalidation)
0.6803 ± 0.0062
Cross-validation details (10-fold Crossvalidation)
44819
Per class
Cross-validation details (10-fold Crossvalidation)
0.6474 ± 0.0103
Per class
Cross-validation details (10-fold Crossvalidation)
0.6803 ± 0.0062
Cross-validation details (10-fold Crossvalidation)
1.3491 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.7505 ± 0.0052
Cross-validation details (10-fold Crossvalidation)
0.4377 ± 0
Cross-validation details (10-fold Crossvalidation)
0.3791 ± 0.0026
Cross-validation details (10-fold Crossvalidation)
0.866 ± 0.006
Cross-validation details (10-fold Crossvalidation)
0.5035 ± 0.0055
Cross-validation details (10-fold Crossvalidation)