DEVELOPMENT... OpenML
Run
141241

Run 141241

Task 244 (Supervised Classification) mfeat-fourier 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)_I40
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
0.9601
Per class
Build CPU time
27.708
Build memory
896036480
F measure
0.824
Per class
Kappa
0.8045
KB relative information score
544.9608
Mean absolute error
0.0361
Mean prior absolute error
0.18
Number of instances
660
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8265
Per class
Predictive accuracy
0.8242
Prior entropy
3.3219
Recall
0.8242
Per class
Relative absolute error
0.2007
Root mean prior squared error
0.3
Root mean squared error
0.1768
Root relative squared error
0.5895
SciMark benchmark
940.5101

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