Run
61446

Run 61446

Task 2102 (Learning Curve) eucalyptus Uploaded 16-11-2014 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_BFTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.BFTree(2)_Ctrue
weka.BFTree(2)_M2
weka.BFTree(2)_N5
weka.BFTree(2)_PPOSTPRUNED
weka.BFTree(2)_S1
weka.MultiBoostAB_BFTree(2)_C3
weka.MultiBoostAB_BFTree(2)_P100
weka.MultiBoostAB_BFTree(2)_S1
weka.MultiBoostAB_BFTree(2)_I10
weka.MultiBoostAB_BFTree(2)_Wweka.classifiers.trees.BFTree

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
0.8767 ± 0.0251
Per class
Build CPU time
1.2338
Build memory
1086430136.3
F measure
0.6573 ± 0.0545
Per class
Kappa
0.5616 ± 0.0676
KB relative information score
0.5946 ± 0.0543
Mean absolute error
0.1392 ± 0.0183
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
0.6615 ± 0.0539
Per class
Predictive accuracy
0.6603 ± 0.052
Prior entropy
2.2621 ± 0.0043
Recall
0.6603 ± 0.052
Per class
Relative absolute error
0.4445 ± 0.0582
Root mean prior squared error
0.3957 ± 0.0003
Root mean squared error
0.3431 ± 0.0278
Root relative squared error
0.867 ± 0.07
SciMark benchmark
1592.7924