DEVELOPMENT... OpenML
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140780

Run 140780

Task 3054 (Supervised Classification) monks-problems-2 Uploaded 31-12-2014 by Felicia West
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weka.AdaBoostM1_SMO_PolyKernel(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_SMO_PolyKernel(2)_I20
weka.AdaBoostM1_SMO_PolyKernel(2)_P100
weka.AdaBoostM1_SMO_PolyKernel(2)_S1
weka.AdaBoostM1_SMO_PolyKernel(2)_Wweka.classifiers.functions.SMO
weka.SMO_PolyKernel(7)_C1.0
weka.SMO_PolyKernel(7)_L0.001
weka.SMO_PolyKernel(7)_N0
weka.SMO_PolyKernel(7)_P1.0E-12
weka.SMO_PolyKernel(7)_V-1
weka.SMO_PolyKernel(7)_W1

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
0.7247
Per class
Build CPU time
0.263
Build memory
57395480
F measure
0.6494
Per class
Kappa
0.2408
KB relative information score
29.329
Mean absolute error
0.3923
Mean prior absolute error
0.4588
Number of instances
198
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.682
Per class
Predictive accuracy
0.6869
Prior entropy
0.9279
Recall
0.6869
Per class
Relative absolute error
0.8549
Root mean prior squared error
0.4831
Root mean squared error
0.449
Root relative squared error
0.9293
SciMark benchmark
937.3768

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