Run
9920062

Run 9920062

Task 6 (Supervised Classification) letter Uploaded 25-12-2018 by Pieter Gijsbers
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Flow

sklearn.pipeline.Pipeline(imputation=preprocessing.ConditionalImputer2,cate ncoding=preprocessing.MultiLabelEncoder,variencethreshold=sklearn.feature_s election.variance_threshold.VarianceThreshold,clf=sklearn.ensemble.forest.R andomForestClassifier)(1)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(45)_bootstrapfalse
sklearn.ensemble.forest.RandomForestClassifier(45)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(45)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(45)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(45)_max_features0.7839755111051104
sklearn.ensemble.forest.RandomForestClassifier(45)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(45)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(45)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(45)_min_samples_leaf6
sklearn.ensemble.forest.RandomForestClassifier(45)_min_samples_split9
sklearn.ensemble.forest.RandomForestClassifier(45)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(45)_n_estimators300
sklearn.ensemble.forest.RandomForestClassifier(45)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(45)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(45)_random_state57428
sklearn.ensemble.forest.RandomForestClassifier(45)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(45)_warm_startfalse
preprocessing.ConditionalImputer2(1)_axis0
preprocessing.ConditionalImputer2(1)_categorical_features[]
preprocessing.ConditionalImputer2(1)_copytrue
preprocessing.ConditionalImputer2(1)_fill_empty0
preprocessing.ConditionalImputer2(1)_missing_values"NaN"
preprocessing.ConditionalImputer2(1)_strategy"mean"
preprocessing.ConditionalImputer2(1)_strategy_nominal"most_frequent"
preprocessing.ConditionalImputer2(1)_verbose0
sklearn.feature_selection.variance_threshold.VarianceThreshold(20)_threshold0.0
sklearn.pipeline.Pipeline(imputation=preprocessing.ConditionalImputer2,catencoding=preprocessing.MultiLabelEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.ensemble.forest.RandomForestClassifier)(1)_memorynull
preprocessing.MultiLabelEncoder(1)_colsnull

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

0.9989 ± 0.0002
Per class
Cross-validation details (10-fold Crossvalidation)
0.9353 ± 0.0045
Per class
Cross-validation details (10-fold Crossvalidation)
0.9326 ± 0.0047
Cross-validation details (10-fold Crossvalidation)
18097.2405 ± 5.9222
Cross-validation details (10-fold Crossvalidation)
0.0148 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
0.074 ± 0
Cross-validation details (10-fold Crossvalidation)
20000
Per class
Cross-validation details (10-fold Crossvalidation)
0.9358 ± 0.0042
Per class
Cross-validation details (10-fold Crossvalidation)
0.9352 ± 0.0045
Cross-validation details (10-fold Crossvalidation)
4.6998
Cross-validation details (10-fold Crossvalidation)
0.9352 ± 0.0045
Per class
Cross-validation details (10-fold Crossvalidation)
0.2001 ± 0.0056
Cross-validation details (10-fold Crossvalidation)
0.1923 ± 0
Cross-validation details (10-fold Crossvalidation)
0.0711 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
0.3699 ± 0.0068
Cross-validation details (10-fold Crossvalidation)