Run
133988

Run 133988

Task 3887 (Supervised Classification) analcatdata_germangss 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
0.9598
Per class
Cross-validation details (10-fold Crossvalidation)
Build CPU time
0.032
Cross-validation details (10-fold Crossvalidation)
Build memory
1124059532.8
Cross-validation details (10-fold Crossvalidation)
F measure
0.9034
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7187
Cross-validation details (10-fold Crossvalidation)
KB relative information score
233.7164
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1439
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3495
Cross-validation details (10-fold Crossvalidation)
Number of instances
400
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
0.9028
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.905
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7716
Cross-validation details (10-fold Crossvalidation)
Recall
0.905
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4117
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4176
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2551
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6108
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
939.084