Run
51960

Run 51960

Task 1730 (Learning Curve) credit-g 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
0.7193 ± 0.0402
Per class
Build CPU time
0.0327
Build memory
2570172711.8222
F measure
0.7072 ± 0.0309
Per class
Kappa
0.2871 ± 0.0746
KB relative information score
0.2769 ± 0.0742
Mean absolute error
0.2825 ± 0.0289
Mean prior absolute error
0.4202
Number of instances
1000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.7029 ± 0.033
Per class
Predictive accuracy
0.716 ± 0.0313
Prior entropy
0.8813
Recall
0.716 ± 0.0313
Per class
Relative absolute error
0.6724 ± 0.0687
Root mean prior squared error
0.4583
Root mean squared error
0.5159 ± 0.0272
Root relative squared error
1.1259 ± 0.0593
SciMark benchmark
1645.1824