Run
137396

Run 137396

Task 3705 (Supervised Classification) autoHorse Uploaded 31-12-2014 by Joaquin Vanschoren
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Flow

weka.AdaBoostM1_REPTree(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_REPTree(2)_I160
weka.AdaBoostM1_REPTree(2)_P100
weka.AdaBoostM1_REPTree(2)_S1
weka.AdaBoostM1_REPTree(2)_Wweka.classifiers.trees.REPTree
weka.REPTree(5)_I0.0
weka.REPTree(5)_L-1
weka.REPTree(5)_M2
weka.REPTree(5)_N3
weka.REPTree(5)_S1
weka.REPTree(5)_V0.001

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
0.9811
Per class
Cross-validation details (10-fold Crossvalidation)
Build CPU time
0.0431
Cross-validation details (10-fold Crossvalidation)
Build memory
149287360
Cross-validation details (10-fold Crossvalidation)
F measure
0.9707
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9393
Cross-validation details (10-fold Crossvalidation)
KB relative information score
189.5457
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0365
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4821
Cross-validation details (10-fold Crossvalidation)
Number of instances
205
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
0.9707
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9707
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9742
Cross-validation details (10-fold Crossvalidation)
Recall
0.9707
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0756
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4909
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1638
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.3337
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
945.1987