Run
1852388

Run 1852388

Task 145677 (Supervised Classification) Bioresponse Uploaded 13-03-2017 by Stanley Clark
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • Mon_Mar_13_10.54.09_2017 NumPy_1.12.0. Python_3.5.2. run_task SciPy_0.18.1. sklearn.pipeline.Pipeline Sklearn_0.18.1.
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.Standar dScaler,selectfrommodel=sklearn.feature_selection.from_model.SelectFromMode l(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),logisticregressio n=sklearn.linear_model.logistic.LogisticRegression)(1)Automatically created scikit-learn flow.
sklearn.linear_model.logistic.LogisticRegression(3)_C1.0
sklearn.linear_model.logistic.LogisticRegression(3)_class_weightNone
sklearn.linear_model.logistic.LogisticRegression(3)_dualFalse
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_jobs1
sklearn.linear_model.logistic.LogisticRegression(3)_penaltyl2
sklearn.linear_model.logistic.LogisticRegression(3)_random_stateNone
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.ensemble.forest.ExtraTreesClassifier(5)_bootstrapFalse
sklearn.ensemble.forest.ExtraTreesClassifier(5)_class_weightNone
sklearn.ensemble.forest.ExtraTreesClassifier(5)_criteriongini
sklearn.ensemble.forest.ExtraTreesClassifier(5)_max_depthNone
sklearn.ensemble.forest.ExtraTreesClassifier(5)_max_featuresauto
sklearn.ensemble.forest.ExtraTreesClassifier(5)_max_leaf_nodesNone
sklearn.ensemble.forest.ExtraTreesClassifier(5)_min_impurity_split1e-07
sklearn.ensemble.forest.ExtraTreesClassifier(5)_min_samples_leaf1
sklearn.ensemble.forest.ExtraTreesClassifier(5)_min_samples_split2
sklearn.ensemble.forest.ExtraTreesClassifier(5)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.ExtraTreesClassifier(5)_n_estimators10
sklearn.ensemble.forest.ExtraTreesClassifier(5)_n_jobs1
sklearn.ensemble.forest.ExtraTreesClassifier(5)_oob_scoreFalse
sklearn.ensemble.forest.ExtraTreesClassifier(5)_random_stateNone
sklearn.ensemble.forest.ExtraTreesClassifier(5)_verbose0
sklearn.ensemble.forest.ExtraTreesClassifier(5)_warm_startFalse
sklearn.preprocessing.data.StandardScaler(1)_copyTrue
sklearn.preprocessing.data.StandardScaler(1)_with_meanTrue
sklearn.preprocessing.data.StandardScaler(1)_with_stdTrue
sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier)(1)_estimatorExtraTreesClassifier(bootstrap=False, class_weight=None, criterion='gini', max_depth=None, max_features='auto', max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=1, oob_score=False, random_state=None, verbose=0, warm_start=False)
sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier)(1)_prefitFalse
sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier)(1)_thresholdNone
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,selectfrommodel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),logisticregression=sklearn.linear_model.logistic.LogisticRegression)(1)_steps[('standardscaler', StandardScaler(copy=True, with_mean=True, with_std=True)), ('selectfrommodel', SelectFromModel(estimator=ExtraTreesClassifier(bootstrap=False, class_weight=None, criterion='gini', max_depth=None, max_features='auto', max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=1, oob_score=False, random_state=None, verbose=0, warm_start=False), prefit=False, threshold=None)), ('logisticregression', LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True, intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1, penalty='l2', random_state=None, 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
0.8221
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7609
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5178
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1644.8247
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.287
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4964
Cross-validation details (10-fold Crossvalidation)
Number of instances
3751
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.761
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7614
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9948
Cross-validation details (10-fold Crossvalidation)
Recall
0.7614
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5782
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4982
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4211
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8452
Cross-validation details (10-fold Crossvalidation)