Run
10560799

Run 10560799

Task 10101 (Supervised Classification) blood-transfusion-service-center Uploaded 07-09-2021 by Prince Mishra
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Flow

sklearn.ensemble._forest.RandomForestClassifier(11)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(11)_bootstraptrue
sklearn.ensemble._forest.RandomForestClassifier(11)_ccp_alpha0.0
sklearn.ensemble._forest.RandomForestClassifier(11)_class_weightnull
sklearn.ensemble._forest.RandomForestClassifier(11)_criterion"gini"
sklearn.ensemble._forest.RandomForestClassifier(11)_max_depthnull
sklearn.ensemble._forest.RandomForestClassifier(11)_max_features"auto"
sklearn.ensemble._forest.RandomForestClassifier(11)_max_leaf_nodesnull
sklearn.ensemble._forest.RandomForestClassifier(11)_max_samplesnull
sklearn.ensemble._forest.RandomForestClassifier(11)_min_impurity_decrease0.0
sklearn.ensemble._forest.RandomForestClassifier(11)_min_impurity_splitnull
sklearn.ensemble._forest.RandomForestClassifier(11)_min_samples_leaf1
sklearn.ensemble._forest.RandomForestClassifier(11)_min_samples_split2
sklearn.ensemble._forest.RandomForestClassifier(11)_min_weight_fraction_leaf0.0
sklearn.ensemble._forest.RandomForestClassifier(11)_n_estimators100
sklearn.ensemble._forest.RandomForestClassifier(11)_n_jobsnull
sklearn.ensemble._forest.RandomForestClassifier(11)_oob_scorefalse
sklearn.ensemble._forest.RandomForestClassifier(11)_random_state52904
sklearn.ensemble._forest.RandomForestClassifier(11)_verbose0
sklearn.ensemble._forest.RandomForestClassifier(11)_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

0.6807 ± 0.0646
Per class
Cross-validation details (10-fold Crossvalidation)
0.7295 ± 0.045
Per class
Cross-validation details (10-fold Crossvalidation)
0.2161 ± 0.1312
Cross-validation details (10-fold Crossvalidation)
0.0854 ± 0.0967
Cross-validation details (10-fold Crossvalidation)
0.3042 ± 0.0253
Cross-validation details (10-fold Crossvalidation)
0.363 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
0.7487 ± 0.0421
Cross-validation details (10-fold Crossvalidation)
748
Per class
Cross-validation details (10-fold Crossvalidation)
0.7209 ± 0.0503
Per class
Cross-validation details (10-fold Crossvalidation)
0.7487 ± 0.0421
Cross-validation details (10-fold Crossvalidation)
0.7916 ± 0.0072
Cross-validation details (10-fold Crossvalidation)
0.8379 ± 0.0694
Cross-validation details (10-fold Crossvalidation)
0.4258 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
0.4289 ± 0.0301
Cross-validation details (10-fold Crossvalidation)
1.0072 ± 0.0714
Cross-validation details (10-fold Crossvalidation)
0.5955 ± 0.0627
Cross-validation details (10-fold Crossvalidation)