Run
4206

Run 4206

Task 119 (Supervised Classification) diabetes Uploaded 01-03-2021 by Test Test
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Flow

sklearn.ensemble._forest.RandomForestClassifier(4)A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting. The sub-sample size is controlled with the `max_samples` parameter if `bootstrap=True` (default), otherwise the whole dataset is used to build each tree.
sklearn.ensemble._forest.RandomForestClassifier(4)_bootstraptrue
sklearn.ensemble._forest.RandomForestClassifier(4)_ccp_alpha0.0
sklearn.ensemble._forest.RandomForestClassifier(4)_class_weightnull
sklearn.ensemble._forest.RandomForestClassifier(4)_criterion"gini"
sklearn.ensemble._forest.RandomForestClassifier(4)_max_depthnull
sklearn.ensemble._forest.RandomForestClassifier(4)_max_features"auto"
sklearn.ensemble._forest.RandomForestClassifier(4)_max_leaf_nodesnull
sklearn.ensemble._forest.RandomForestClassifier(4)_max_samplesnull
sklearn.ensemble._forest.RandomForestClassifier(4)_min_impurity_decrease0.0
sklearn.ensemble._forest.RandomForestClassifier(4)_min_impurity_splitnull
sklearn.ensemble._forest.RandomForestClassifier(4)_min_samples_leaf1
sklearn.ensemble._forest.RandomForestClassifier(4)_min_samples_split2
sklearn.ensemble._forest.RandomForestClassifier(4)_min_weight_fraction_leaf0.0
sklearn.ensemble._forest.RandomForestClassifier(4)_n_estimators100
sklearn.ensemble._forest.RandomForestClassifier(4)_n_jobsnull
sklearn.ensemble._forest.RandomForestClassifier(4)_oob_scorefalse
sklearn.ensemble._forest.RandomForestClassifier(4)_random_state57881
sklearn.ensemble._forest.RandomForestClassifier(4)_verbose0
sklearn.ensemble._forest.RandomForestClassifier(4)_warm_startfalse

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.

18 Evaluation measures

0.8163
Per class
Cross-validation details (10% Holdout set)
0.78
Per class
Cross-validation details (10% Holdout set)
0.5202
Cross-validation details (10% Holdout set)
0.3159
Cross-validation details (10% Holdout set)
0.3195
Cross-validation details (10% Holdout set)
0.4589
Cross-validation details (10% Holdout set)
0.7826
Cross-validation details (10% Holdout set)
253
Per class
Cross-validation details (10% Holdout set)
0.7794
Per class
Cross-validation details (10% Holdout set)
0.7826
Cross-validation details (10% Holdout set)
0.9463
Cross-validation details (10% Holdout set)
0.6963
Cross-validation details (10% Holdout set)
0.4813
Cross-validation details (10% Holdout set)
0.407
Cross-validation details (10% Holdout set)
0.8458
Cross-validation details (10% Holdout set)
0.7547
Cross-validation details (10% Holdout set)