DEVELOPMENT... OpenML
Run
53358

Run 53358

Task 1727 (Learning Curve) optdigits Uploaded 08-11-2014 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
0.9886 ± 0.0025
Per class
Build CPU time
0.1755
Build memory
1954083472.4
F measure
0.8739 ± 0.0157
Per class
Kappa
0.8596 ± 0.018
KB relative information score
0.859 ± 0.0111
Mean absolute error
0.0368 ± 0.0025
Mean prior absolute error
0.18 ± 0
Number of instances
5620
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.8746 ± 0.0139
Per class
Predictive accuracy
0.8737 ± 0.0162
Prior entropy
3.3218 ± 0.0001
Recall
0.8737 ± 0.0162
Per class
Relative absolute error
0.2045 ± 0.0139
Root mean prior squared error
0.3 ± 0
Root mean squared error
0.1368 ± 0.0068
Root relative squared error
0.4559 ± 0.0227
SciMark benchmark
1206.3605