Run
503506

Run 503506

Task 10041 (Learning Curve) ada_agnostic Uploaded 28-12-2015 by Jan van Rijn
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Flow

weka.AdaBoostM1_J48(3)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.J48(33)_C0.25
weka.J48(33)_M2
weka.AdaBoostM1_J48(3)_P100
weka.AdaBoostM1_J48(3)_S1
weka.AdaBoostM1_J48(3)_I10
weka.AdaBoostM1_J48(3)_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.

22 Evaluation measures

Area under ROC curve
0.8357 ± 0.0158
Per class
F measure
0.8153 ± 0.0147
Per class
Kappa
0.4995 ± 0.0393
KB relative information score
2105.4196 ± 17.317
Mean absolute error
0.1786 ± 0.012
Mean prior absolute error
0.3732 ± 0.0004
Number of instances
4562
Per class
OS information
[Sun Microsystems Inc., 1.6.0_37, amd64, Linux, 3.5.0-54-generic]
Precision
0.8136 ± 0.0147
Per class
Predictive accuracy
0.8174 ± 0.0151
Prior entropy
0.8085
Recall
0.8174 ± 0.0151
Per class
Relative absolute error
0.4785 ± 0.0322
Root mean prior squared error
0.4319 ± 0.0005
Root mean squared error
0.4052 ± 0.0156
Root relative squared error
0.9381 ± 0.0363
SciMark benchmark
1678.2337
UserCPU time millis
4360
UserCPU time millis testing
30
UserCPU time millis training
4330