DEVELOPMENT... OpenML
Run
140075

Run 140075

Task 1768 (Supervised Classification) labor Uploaded 31-12-2014 by Felicia West
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Flow

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)_I10
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
0.8901
Per class
Build CPU time
0.0263
Build memory
599251321.5158
F measure
0.8908
Per class
Kappa
0.7596
KB relative information score
215.4027
Mean absolute error
0.1057
Mean prior absolute error
0.457
Number of instances
285
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8907
Per class
Predictive accuracy
0.8912
Prior entropy
0.9393
Recall
0.8912
Per class
Relative absolute error
0.2312
Root mean prior squared error
0.4773
Root mean squared error
0.3171
Root relative squared error
0.6644
SciMark benchmark
925.181