Run
10228370

Run 10228370

Task 2077 (Supervised Classification) baseball Uploaded 04-06-2019 by Peter Fontana
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Flow

sklearn.pipeline.Pipeline(Imputer=sklearn.impute.SimpleImputer,fs=sklearn.f eature_selection.univariate_selection.SelectPercentile,rf=sklearn.ensemble. forest.RandomForestClassifier)(1)Automatically created scikit-learn flow.
sklearn.impute.SimpleImputer(10)_copytrue
sklearn.impute.SimpleImputer(10)_fill_valuenull
sklearn.impute.SimpleImputer(10)_missing_valuesNaN
sklearn.impute.SimpleImputer(10)_strategy"constant"
sklearn.impute.SimpleImputer(10)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(51)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(51)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(51)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(51)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(51)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(51)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(51)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(51)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(51)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(51)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(51)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(51)_n_estimators100
sklearn.ensemble.forest.RandomForestClassifier(51)_n_jobsnull
sklearn.ensemble.forest.RandomForestClassifier(51)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(51)_random_state31461
sklearn.ensemble.forest.RandomForestClassifier(51)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(51)_warm_startfalse
sklearn.feature_selection.univariate_selection.SelectPercentile(3)_percentile80
sklearn.feature_selection.univariate_selection.SelectPercentile(3)_score_func{"oml-python:serialized_object": "function", "value": "sklearn.feature_selection.univariate_selection.f_classif"}
sklearn.pipeline.Pipeline(Imputer=sklearn.impute.SimpleImputer,fs=sklearn.feature_selection.univariate_selection.SelectPercentile,rf=sklearn.ensemble.forest.RandomForestClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(Imputer=sklearn.impute.SimpleImputer,fs=sklearn.feature_selection.univariate_selection.SelectPercentile,rf=sklearn.ensemble.forest.RandomForestClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "Imputer", "step_name": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "fs", "step_name": "fs"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "rf", "step_name": "rf"}}]

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
0.951 ± 0.0313
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9278 ± 0.014
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5684 ± 0.0858
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.353 ± 0.1194
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0639 ± 0.0074
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1164 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Number of instances
1340
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9239 ± 0.016
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9351 ± 0.0127
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.5401 ± 0.0169
Cross-validation details (10-fold Crossvalidation)
Recall
0.9351 ± 0.0127
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5493 ± 0.0668
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2405 ± 0.0047
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1793 ± 0.0144
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7456 ± 0.065
Cross-validation details (10-fold Crossvalidation)