DEVELOPMENT... OpenML
Run
59042

Run 59042

Task 1731 (Learning Curve) pendigits Uploaded 15-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.RacedIncrementalLogitBoost_DecisionStump(2)Eibe Frank, Geoffrey Holmes, Richard Kirkby, Mark Hall: Racing committees for large datasets. In: Proceedings of the 5th International Conferenceon Discovery Science, 153-164, 2002.
weka.RacedIncrementalLogitBoost_DecisionStump(2)_C500
weka.RacedIncrementalLogitBoost_DecisionStump(2)_M2000
weka.RacedIncrementalLogitBoost_DecisionStump(2)_V1000
weka.RacedIncrementalLogitBoost_DecisionStump(2)_P1
weka.RacedIncrementalLogitBoost_DecisionStump(2)_S1
weka.RacedIncrementalLogitBoost_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump

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
0.9923 ± 0.0016
Per class
Build CPU time
0.154
Build memory
2841779982.45
F measure
0.8943 ± 0.0136
Per class
Kappa
0.8828 ± 0.0146
KB relative information score
0.8862 ± 0.0131
Mean absolute error
0.0299 ± 0.0035
Mean prior absolute error
0.18 ± 0
Number of instances
10992
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.8944 ± 0.0134
Per class
Predictive accuracy
0.8946 ± 0.0131
Prior entropy
3.3208 ± 0.0002
Recall
0.8946 ± 0.0131
Per class
Relative absolute error
0.1661 ± 0.0197
Root mean prior squared error
0.3 ± 0
Root mean squared error
0.125 ± 0.0067
Root relative squared error
0.4167 ± 0.0222
SciMark benchmark
1769.7895