Run
57192

Run 57192

Task 1731 (Learning Curve) pendigits Uploaded 12-11-2014 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.AdaBoostM1_IBk(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_IBk(2)_I10
weka.AdaBoostM1_IBk(2)_P100
weka.AdaBoostM1_IBk(2)_S1
weka.AdaBoostM1_IBk(2)_Wweka.classifiers.lazy.IBk
weka.IBk(2)_Atrue
weka.IBk(2)_K1
weka.IBk(2)_W0

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
0.9965 ± 0.0011
Per class
Build CPU time
0.6234
Build memory
644610320.85
F measure
0.9937 ± 0.0019
Per class
Kappa
0.993 ± 0.0021
KB relative information score
0.993 ± 0.002
Mean absolute error
0.0014 ± 0.0004
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
0.9937 ± 0.0019
Per class
Predictive accuracy
0.9937 ± 0.0019
Prior entropy
3.3208 ± 0.0002
Recall
0.9937 ± 0.0019
Per class
Relative absolute error
0.008 ± 0.0021
Root mean prior squared error
0.3 ± 0
Root mean squared error
0.0354 ± 0.0055
Root relative squared error
0.1181 ± 0.0182
SciMark benchmark
1732.6592