Run
10587913

Run 10587913

Task 3954 (Supervised Classification) MagicTelescope Uploaded 30-07-2022 by Hector Haffenden
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Flow

sklearn.ensemble._forest.RandomForestClassifier(10)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(10)_bootstraptrue
sklearn.ensemble._forest.RandomForestClassifier(10)_ccp_alpha0.0
sklearn.ensemble._forest.RandomForestClassifier(10)_class_weightnull
sklearn.ensemble._forest.RandomForestClassifier(10)_criterion"gini"
sklearn.ensemble._forest.RandomForestClassifier(10)_max_depthnull
sklearn.ensemble._forest.RandomForestClassifier(10)_max_features"auto"
sklearn.ensemble._forest.RandomForestClassifier(10)_max_leaf_nodesnull
sklearn.ensemble._forest.RandomForestClassifier(10)_max_samplesnull
sklearn.ensemble._forest.RandomForestClassifier(10)_min_impurity_decrease0.0
sklearn.ensemble._forest.RandomForestClassifier(10)_min_impurity_splitnull
sklearn.ensemble._forest.RandomForestClassifier(10)_min_samples_leaf1
sklearn.ensemble._forest.RandomForestClassifier(10)_min_samples_split2
sklearn.ensemble._forest.RandomForestClassifier(10)_min_weight_fraction_leaf0.0
sklearn.ensemble._forest.RandomForestClassifier(10)_n_estimators100
sklearn.ensemble._forest.RandomForestClassifier(10)_n_jobsnull
sklearn.ensemble._forest.RandomForestClassifier(10)_oob_scorefalse
sklearn.ensemble._forest.RandomForestClassifier(10)_random_state4123
sklearn.ensemble._forest.RandomForestClassifier(10)_verbose0
sklearn.ensemble._forest.RandomForestClassifier(10)_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

0.9364 ± 0.0061
Per class
Cross-validation details (10-fold Crossvalidation)
0.8801 ± 0.0057
Per class
Cross-validation details (10-fold Crossvalidation)
0.7339 ± 0.013
Cross-validation details (10-fold Crossvalidation)
0.5966 ± 0.0096
Cross-validation details (10-fold Crossvalidation)
0.1946 ± 0.0039
Cross-validation details (10-fold Crossvalidation)
0.456 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.8821 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
19020
Per class
Cross-validation details (10-fold Crossvalidation)
0.8819 ± 0.0051
Per class
Cross-validation details (10-fold Crossvalidation)
0.8821 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
0.9355 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.4267 ± 0.0085
Cross-validation details (10-fold Crossvalidation)
0.4775 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.2995 ± 0.0057
Cross-validation details (10-fold Crossvalidation)
0.6272 ± 0.0119
Cross-validation details (10-fold Crossvalidation)
0.8567 ± 0.008
Cross-validation details (10-fold Crossvalidation)