Run
10423863

Run 10423863

Task 12 (Supervised Classification) mfeat-factors Uploaded 05-12-2019 by Mervyn Naidoo
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Flow

sklearn.ensemble.forest.RandomForestClassifier(60)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 use averaging to improve the predictive accuracy and control over-fitting. The sub-sample size is always the same as the original input sample size but the samples are drawn with replacement if `bootstrap=True` (default).
sklearn.ensemble.forest.RandomForestClassifier(60)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(60)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(60)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(60)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(60)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(60)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(60)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(60)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(60)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(60)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(60)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(60)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(60)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(60)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(60)_random_state37061
sklearn.ensemble.forest.RandomForestClassifier(60)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(60)_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

Area under ROC curve
0.9948 ± 0.0031
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9515 ± 0.0064
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9461 ± 0.0074
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.8931 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0343 ± 0.0024
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.9515 ± 0.0067
Cross-validation details (10-fold Crossvalidation)
Number of instances
2000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9518 ± 0.0061
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9515 ± 0.0067
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1906 ± 0.0135
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1059 ± 0.0044
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.3531 ± 0.0146
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.9515 ± 0.0067
Cross-validation details (10-fold Crossvalidation)