Run
8657879

Run 8657879

Task 146064 (Supervised Classification) monks-problems-1 Uploaded 16-12-2017 by OpenML_Bot R
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  • botV1 mlrRandomBot sciBenchV1.0
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Flow

mlr.classif.ranger(16)Learner mlr.classif.ranger from package(s) ranger.
mlr.classif.ranger(16)_num.trees1030
mlr.classif.ranger(16)_mtry4
mlr.classif.ranger(16)_min.node.size191
mlr.classif.ranger(16)_sample.fraction0.27702718952205
mlr.classif.ranger(16)_num.threads1
mlr.classif.ranger(16)_verboseFALSE
mlr.classif.ranger(16)_openml.seed1
mlr.classif.ranger(16)_openml.kindMersenne-Twister
mlr.classif.ranger(16)_openml.normal.kindInversion

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.

21 Evaluation measures

Area under ROC curve
0.4971
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.4774
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.0036
KB relative information score
-0.0108
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.5
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.5
Cross-validation details (10-fold Crossvalidation)
Number of instances
556
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.4979
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4982
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1
Cross-validation details (10-fold Crossvalidation)
Recall
0.4982
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.5
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
1370.7842
UserCPU time millis
0.551
UserCPU time millis testing
0.108
UserCPU time millis training
0.443