Run
107543

Run 107543

Task 2353 (Supervised Classification) meta_batchincremental.arff Uploaded 09-12-2014 by Joaquin Vanschoren
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Flow

weka.AdaBoostM1_BFTree(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_BFTree(2)_I40
weka.AdaBoostM1_BFTree(2)_P100
weka.AdaBoostM1_BFTree(2)_S1
weka.AdaBoostM1_BFTree(2)_Wweka.classifiers.trees.BFTree
weka.BFTree(2)_Ctrue
weka.BFTree(2)_M2
weka.BFTree(2)_N5
weka.BFTree(2)_PPOSTPRUNED
weka.BFTree(2)_S1

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
0.7591
Per class
Cross-validation details (33% Holdout set)
Build CPU time
0.725
Cross-validation details (33% Holdout set)
Build memory
1920770536
Cross-validation details (33% Holdout set)
F measure
0.7153
Per class
Cross-validation details (33% Holdout set)
Kappa
0.2821
Cross-validation details (33% Holdout set)
KB relative information score
5.0358
Cross-validation details (33% Holdout set)
Mean absolute error
0.1451
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.2249
Cross-validation details (33% Holdout set)
Number of instances
24
Per class
Cross-validation details (33% Holdout set)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7402
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.7083
Cross-validation details (33% Holdout set)
Prior entropy
1.3842
Cross-validation details (33% Holdout set)
Recall
0.7083
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.6454
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.3095
Cross-validation details (33% Holdout set)
Root mean squared error
0.3792
Cross-validation details (33% Holdout set)
Root relative squared error
1.2253
Cross-validation details (33% Holdout set)
SciMark benchmark
949.8157