Run
9920089

Run 9920089

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)_bootstraptrue
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_features0.13249847630744993
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_leaf2
sklearn.ensemble.forest.RandomForestClassifier(45)_min_samples_split4
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_state85030
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

Area under ROC curve
0.9995 ± 0
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9619 ± 0.0019
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9603 ± 0.002
Cross-validation details (10-fold Crossvalidation)
KB relative information score
17594.0089 ± 4.0755
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0201 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.074 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
20000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9623 ± 0.0018
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9619 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
Prior entropy
4.6998
Cross-validation details (10-fold Crossvalidation)
Recall
0.9619 ± 0.0019
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2722 ± 0.0041
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.1923 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0765 ± 0.0009
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.398 ± 0.0044
Cross-validation details (10-fold Crossvalidation)