Run
25242

Run 25242

Task 90 (Learning Curve) credit-g Uploaded 17-08-2014 by Jan van Rijn
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Flow

weka.SMO_PolyKernel(6)J. Platt: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning, 1998. S.S. Keerthi, S.K. Shevade, C. Bhattacharyya, K.R.K. Murthy (2001). Improvements to Platt's SMO Algorithm for SVM Classifier Design. Neural Computation. 13(3):637-649. Trevor Hastie, Robert Tibshirani: Classification by Pairwise Coupling. In: Advances in Neural Information Processing Systems, 1998.
weka.PolyKernel(4)_C250007
weka.PolyKernel(4)_E1.0
weka.SMO_PolyKernel(6)_C1.0
weka.SMO_PolyKernel(6)_Kweka.classifiers.functions.supportVector.PolyKernel
weka.SMO_PolyKernel(6)_L0.001
weka.SMO_PolyKernel(6)_N0
weka.SMO_PolyKernel(6)_P1.0E-12
weka.SMO_PolyKernel(6)_V-1
weka.SMO_PolyKernel(6)_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

0.6679 ± 0.0494
Per class
0.1058
4671522539.9467
0.7385 ± 0.0408
Per class
0.3599 ± 0.1008
0.3596 ± 0.0988
0.2508 ± 0.0387
0.4202
10000
Per class
[Oracle Corporation, 1.7.0_55, amd64, Linux, 3.8.0-44-generic]
0.7362 ± 0.043
Per class
0.7492 ± 0.0387
0.8813
0.7492 ± 0.0387
Per class
0.5969 ± 0.0921
0.4583
0.5008 ± 0.0389
1.0928 ± 0.0849
1163.973[672.1543817994253969.5371342043437516.718858767917948.42259692008722713.03194350976]