Run
1849086

Run 1849086

Task 59 (Supervised Classification) iris Uploaded 06-03-2017 by Joaquin Vanschoren
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  • Mon_Mar__6_10.41.11_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(Imputer=sklearn.preprocessing.imputation.Imputer, OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.e nsemble.forest.RandomForestClassifier)(1)Automatically created sub-component.
sklearn.ensemble.forest.RandomForestClassifier(16)_bootstrapTrue
sklearn.ensemble.forest.RandomForestClassifier(16)_class_weightNone
sklearn.ensemble.forest.RandomForestClassifier(16)_criteriongini
sklearn.ensemble.forest.RandomForestClassifier(16)_max_depthNone
sklearn.ensemble.forest.RandomForestClassifier(16)_max_featuresauto
sklearn.ensemble.forest.RandomForestClassifier(16)_max_leaf_nodesNone
sklearn.ensemble.forest.RandomForestClassifier(16)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(16)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(16)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(16)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(16)_oob_scoreFalse
sklearn.ensemble.forest.RandomForestClassifier(16)_random_stateNone
sklearn.ensemble.forest.RandomForestClassifier(16)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(16)_warm_startFalse
sklearn.preprocessing.imputation.Imputer(3)_axis0
sklearn.preprocessing.imputation.Imputer(3)_copyTrue
sklearn.preprocessing.imputation.Imputer(3)_missing_valuesNaN
sklearn.preprocessing.imputation.Imputer(3)_strategymedian
sklearn.preprocessing.imputation.Imputer(3)_verbose0
sklearn.preprocessing.data.OneHotEncoder(3)_categorical_featuresall
sklearn.preprocessing.data.OneHotEncoder(3)_dtype
sklearn.preprocessing.data.OneHotEncoder(3)_handle_unknownignore
sklearn.preprocessing.data.OneHotEncoder(3)_n_valuesauto
sklearn.preprocessing.data.OneHotEncoder(3)_sparseFalse
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier)(1)_steps[('Imputer', Imputer(axis=0, copy=True, missing_values='NaN', strategy='median', verbose=0)), ('OneHotEncoder', OneHotEncoder(categorical_features='all', dtype=, handle_unknown='ignore', n_values='auto', sparse=False)), ('Classifier', RandomForestClassifier(bootstrap=True, 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))]

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
0.9735
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9399
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.91
Cross-validation details (10-fold Crossvalidation)
KB relative information score
131.9491
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0658
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4444
Cross-validation details (10-fold Crossvalidation)
Number of instances
150
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9428
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.94
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.94
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1481
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1924
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4081
Cross-validation details (10-fold Crossvalidation)