Run
106337

Run 106337

Task 277 (Supervised Classification) tae 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)_I10
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
0.6985
Per class
Cross-validation details (33% Holdout set)
Build CPU time
0.085
Cross-validation details (33% Holdout set)
Build memory
586751432
Cross-validation details (33% Holdout set)
F measure
0.5281
Per class
Cross-validation details (33% Holdout set)
Kappa
0.2991
Cross-validation details (33% Holdout set)
KB relative information score
16.0652
Cross-validation details (33% Holdout set)
Mean absolute error
0.3295
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.4445
Cross-validation details (33% Holdout set)
Number of instances
49
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
0.5351
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.5306
Cross-validation details (33% Holdout set)
Prior entropy
1.5845
Cross-validation details (33% Holdout set)
Recall
0.5306
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.7413
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.4715
Cross-validation details (33% Holdout set)
Root mean squared error
0.4922
Cross-validation details (33% Holdout set)
Root relative squared error
1.0439
Cross-validation details (33% Holdout set)
SciMark benchmark
945.384