DEVELOPMENT... OpenML
Run
51812

Run 51812

Task 1722 (Learning Curve) cmc 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
0.6904 ± 0.0161
Per class
Build CPU time
0.0159
Build memory
252365722.24
F measure
0.5282 ± 0.027
Per class
Kappa
0.2661 ± 0.0448
KB relative information score
0.2852 ± 0.0262
Mean absolute error
0.3357 ± 0.0117
Mean prior absolute error
0.4308 ± 0.0004
Number of instances
1473
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.53 ± 0.0262
Per class
Predictive accuracy
0.5309 ± 0.0278
Prior entropy
1.539 ± 0.0029
Recall
0.5309 ± 0.0278
Per class
Relative absolute error
0.7793 ± 0.0275
Root mean prior squared error
0.4641 ± 0.0005
Root mean squared error
0.4796 ± 0.0144
Root relative squared error
1.0333 ± 0.0313
SciMark benchmark
1678.1065