Run
59525

Run 59525

Task 2102 (Learning Curve) eucalyptus Uploaded 15-11-2014 by Joaquin Vanschoren
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Flow

weka.MultiBoostAB_IBk(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.IBk(2)_Atrue
weka.IBk(2)_K1
weka.IBk(2)_W0
weka.MultiBoostAB_IBk(2)_C3
weka.MultiBoostAB_IBk(2)_P100
weka.MultiBoostAB_IBk(2)_S1
weka.MultiBoostAB_IBk(2)_I10
weka.MultiBoostAB_IBk(2)_Wweka.classifiers.lazy.IBk

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
0.6903 ± 0.0246
Per class
Build CPU time
0.0431
Build memory
1166382709.1
F measure
0.5139 ± 0.043
Per class
Kappa
0.3747 ± 0.0494
KB relative information score
0.4209 ± 0.0451
Mean absolute error
0.1971 ± 0.0165
Mean prior absolute error
0.3132 ± 0.0002
Number of instances
736
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.5197 ± 0.0382
Per class
Predictive accuracy
0.5095 ± 0.0417
Prior entropy
2.2621 ± 0.0043
Recall
0.5095 ± 0.0417
Per class
Relative absolute error
0.6293 ± 0.0529
Root mean prior squared error
0.3957 ± 0.0003
Root mean squared error
0.4413 ± 0.019
Root relative squared error
1.1152 ± 0.0482
SciMark benchmark
947.0414