Run
503976

Run 503976

Task 10058 (Learning Curve) ipums_la_98-small Uploaded 29-12-2015 by Joaquin Vanschoren
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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
0.7658 ± 0.0456
Per class
F measure
0.8582 ± 0.0086
Per class
Kappa
0.1965 ± 0.0503
KB relative information score
505.0288 ± 46.3142
Mean absolute error
0.1305 ± 0.0086
Mean prior absolute error
0.1891 ± 0.0003
Number of instances
7485
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8497 ± 0.0096
Per class
Predictive accuracy
0.8692 ± 0.0087
Prior entropy
0.4871
Recall
0.8692 ± 0.0087
Per class
Relative absolute error
0.6902 ± 0.0449
Root mean prior squared error
0.3074 ± 0.0005
Root mean squared error
0.3442 ± 0.0127
Root relative squared error
1.1196 ± 0.0404
SciMark benchmark
914.23
UserCPU time millis
8900
UserCPU time millis testing
50
UserCPU time millis training
8850