Run
65052

Run 65052

Task 2102 (Learning Curve) eucalyptus Uploaded 19-11-2014 by Jan van Rijn
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.MultiBoostAB_JRip(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.JRip(2)_F3
weka.JRip(2)_N2.0
weka.JRip(2)_O2
weka.JRip(2)_S1
weka.MultiBoostAB_JRip(2)_C3
weka.MultiBoostAB_JRip(2)_P100
weka.MultiBoostAB_JRip(2)_S1
weka.MultiBoostAB_JRip(2)_I10
weka.MultiBoostAB_JRip(2)_Wweka.classifiers.rules.JRip

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
0.8734 ± 0.0174
Per class
Build CPU time
0.3765
Build memory
4992550622.3
F measure
0.6494 ± 0.0495
Per class
Kappa
0.5547 ± 0.0631
KB relative information score
0.5736 ± 0.0499
Mean absolute error
0.145 ± 0.0159
Mean prior absolute error
0.3132 ± 0.0002
Number of instances
736
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.6611 ± 0.0493
Per class
Predictive accuracy
0.6576 ± 0.0476
Prior entropy
2.2621 ± 0.0043
Recall
0.6576 ± 0.0476
Per class
Relative absolute error
0.4629 ± 0.0509
Root mean prior squared error
0.3957 ± 0.0003
Root mean squared error
0.3447 ± 0.0214
Root relative squared error
0.8712 ± 0.054
SciMark benchmark
1605.1864