DEVELOPMENT... OpenML
Run
51800

Run 51800

Task 1702 (Learning Curve) kr-vs-kp Uploaded 07-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.MultiBoostAB_REPTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.REPTree(5)_I0.0
weka.REPTree(5)_L-1
weka.REPTree(5)_M2
weka.REPTree(5)_N3
weka.REPTree(5)_S1
weka.REPTree(5)_V0.001
weka.MultiBoostAB_REPTree(2)_C3
weka.MultiBoostAB_REPTree(2)_P100
weka.MultiBoostAB_REPTree(2)_S1
weka.MultiBoostAB_REPTree(2)_I10
weka.MultiBoostAB_REPTree(2)_Wweka.classifiers.trees.REPTree

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
0.997 ± 0.0032
Per class
Build CPU time
0.0484
Build memory
520961576.6667
F measure
0.9925 ± 0.0045
Per class
Kappa
0.9849 ± 0.009
KB relative information score
0.9847 ± 0.0085
Mean absolute error
0.0076 ± 0.0042
Mean prior absolute error
0.499 ± 0.0001
Number of instances
3196
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9925 ± 0.0044
Per class
Predictive accuracy
0.9925 ± 0.0045
Prior entropy
0.9986 ± 0.0002
Recall
0.9925 ± 0.0045
Per class
Relative absolute error
0.0153 ± 0.0084
Root mean prior squared error
0.4995 ± 0.0001
Root mean squared error
0.0846 ± 0.0367
Root relative squared error
0.1693 ± 0.0734
SciMark benchmark
1678.1065