Run
9920580

Run 9920580

Task 6 (Supervised Classification) letter Uploaded 26-12-2018 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"entropy"
sklearn.ensemble.forest.RandomForestClassifier(45)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(45)_max_features0.9913113401777658
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_leaf14
sklearn.ensemble.forest.RandomForestClassifier(45)_min_samples_split6
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_state98443
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

0.9945 ± 0.0006
Per class
Cross-validation details (10-fold Crossvalidation)
0.8421 ± 0.0076
Per class
Cross-validation details (10-fold Crossvalidation)
0.8354 ± 0.0079
Cross-validation details (10-fold Crossvalidation)
17161.6715 ± 8.2501
Cross-validation details (10-fold Crossvalidation)
0.0185 ± 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)
0.8431 ± 0.0073
Per class
Cross-validation details (10-fold Crossvalidation)
0.8417 ± 0.0076
Cross-validation details (10-fold Crossvalidation)
4.6998
Cross-validation details (10-fold Crossvalidation)
0.8417 ± 0.0076
Per class
Cross-validation details (10-fold Crossvalidation)
0.25 ± 0.005
Cross-validation details (10-fold Crossvalidation)
0.1923 ± 0
Cross-validation details (10-fold Crossvalidation)
0.0913 ± 0.0015
Cross-validation details (10-fold Crossvalidation)
0.4745 ± 0.0076
Cross-validation details (10-fold Crossvalidation)