Run
51934

Run 51934

Task 1702 (Learning Curve) kr-vs-kp Uploaded 07-11-2014 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.RealAdaBoost_J48(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
weka.J48(3)_C0.25
weka.J48(3)_M2
weka.RealAdaBoost_J48(1)_P100
weka.RealAdaBoost_J48(1)_H1.0
weka.RealAdaBoost_J48(1)_S1
weka.RealAdaBoost_J48(1)_I10
weka.RealAdaBoost_J48(1)_Wweka.classifiers.trees.J48

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
0.9977 ± 0.0022
Per class
Build CPU time
0.0644
Build memory
507642042.9333
F measure
0.9969 ± 0.0029
Per class
Kappa
0.9937 ± 0.0059
KB relative information score
0.9942 ± 0.0053
Mean absolute error
0.0029 ± 0.0026
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
0.9969 ± 0.0029
Per class
Predictive accuracy
0.9969 ± 0.0029
Prior entropy
0.9986 ± 0.0002
Recall
0.9969 ± 0.0029
Per class
Relative absolute error
0.0058 ± 0.0052
Root mean prior squared error
0.4995 ± 0.0001
Root mean squared error
0.0526 ± 0.0315
Root relative squared error
0.1052 ± 0.0631
SciMark benchmark
1609.6362