Run
133869

Run 133869

Task 3756 (Supervised Classification) visualizing_hamster Uploaded 28-12-2014 by Joaquin Vanschoren
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Flow

weka.AdaBoostM1_RandomForest(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_RandomForest(2)_I10
weka.AdaBoostM1_RandomForest(2)_P100
weka.AdaBoostM1_RandomForest(2)_S1
weka.AdaBoostM1_RandomForest(2)_Wweka.classifiers.trees.RandomForest
weka.RandomForest(2)_I100
weka.RandomForest(2)_K0
weka.RandomForest(2)_S1
weka.RandomForest(2)_num-slots1

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

21 Evaluation measures

Area under ROC curve
0.739
Per class
Cross-validation details (10-fold Crossvalidation)
Build CPU time
0.0158
Cross-validation details (10-fold Crossvalidation)
Build memory
361080349.0411
Cross-validation details (10-fold Crossvalidation)
F measure
0.7107
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4147
Cross-validation details (10-fold Crossvalidation)
KB relative information score
17.5582
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3885
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4955
Cross-validation details (10-fold Crossvalidation)
Number of instances
73
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7115
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7123
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9937
Cross-validation details (10-fold Crossvalidation)
Recall
0.7123
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.784
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4977
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4563
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9168
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
946.9091