Run
2070699

Run 2070699

Task 18 (Supervised Classification) mfeat-morphological Uploaded 19-04-2017 by Jeroen van Hoof
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  • NumPy_1.12.0. Python_3.6.0. run_task SciPy_0.19.0. sklearn.pipeline.Pipeline Sklearn_0.18.1. Wed_Apr_19_16.13.57_2017
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Flow

sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.Standar dScaler,logisticregression=sklearn.linear_model.logistic.LogisticRegression )(1)Automatically created scikit-learn flow.
sklearn.linear_model.logistic.LogisticRegression(3)_C15.0
sklearn.linear_model.logistic.LogisticRegression(3)_class_weightNone
sklearn.linear_model.logistic.LogisticRegression(3)_dualTrue
sklearn.linear_model.logistic.LogisticRegression(3)_fit_interceptTrue
sklearn.linear_model.logistic.LogisticRegression(3)_intercept_scaling1
sklearn.linear_model.logistic.LogisticRegression(3)_max_iter100
sklearn.linear_model.logistic.LogisticRegression(3)_multi_classovr
sklearn.linear_model.logistic.LogisticRegression(3)_n_jobs-1
sklearn.linear_model.logistic.LogisticRegression(3)_penaltyl2
sklearn.linear_model.logistic.LogisticRegression(3)_random_state3
sklearn.linear_model.logistic.LogisticRegression(3)_solverliblinear
sklearn.linear_model.logistic.LogisticRegression(3)_tol0.0001
sklearn.linear_model.logistic.LogisticRegression(3)_verbose0
sklearn.linear_model.logistic.LogisticRegression(3)_warm_startFalse
sklearn.preprocessing.data.StandardScaler(1)_copyTrue
sklearn.preprocessing.data.StandardScaler(1)_with_meanTrue
sklearn.preprocessing.data.StandardScaler(1)_with_stdTrue
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,logisticregression=sklearn.linear_model.logistic.LogisticRegression)(1)_steps[('standardscaler', StandardScaler(copy=True, with_mean=True, with_std=True)), ('logisticregression', LogisticRegression(C=15.0, class_weight=None, dual=True, fit_intercept=True, intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=-1, penalty='l2', random_state=3, solver='liblinear', tol=0.0001, verbose=0, warm_start=False))]

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
0.9605
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7389
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.715
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1341.8702
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0958
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18
Cross-validation details (10-fold Crossvalidation)
Number of instances
2000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7399
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7435
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Recall
0.7435
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5323
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1991
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6637
Cross-validation details (10-fold Crossvalidation)
Total cost