Run
9920563

Run 9920563

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"gini"
sklearn.ensemble.forest.RandomForestClassifier(45)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(45)_max_features0.5567754326663494
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_leaf4
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_state61050
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

0.9994 ± 0.0001
Per class
Cross-validation details (10-fold Crossvalidation)
0.954 ± 0.0044
Per class
Cross-validation details (10-fold Crossvalidation)
0.9521 ± 0.0046
Cross-validation details (10-fold Crossvalidation)
18298.4962 ± 5.1446
Cross-validation details (10-fold Crossvalidation)
0.014 ± 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)
0.9543 ± 0.0043
Per class
Cross-validation details (10-fold Crossvalidation)
0.954 ± 0.0044
Cross-validation details (10-fold Crossvalidation)
4.6998
Cross-validation details (10-fold Crossvalidation)
0.954 ± 0.0044
Per class
Cross-validation details (10-fold Crossvalidation)
0.1895 ± 0.0051
Cross-validation details (10-fold Crossvalidation)
0.1923 ± 0
Cross-validation details (10-fold Crossvalidation)
0.0658 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
0.3421 ± 0.0062
Cross-validation details (10-fold Crossvalidation)