DEVELOPMENT... OpenML
Run
899

Run 899

Task 70 (Learning Curve) balance-scale Uploaded 08-04-2014 by Mandy
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Flow

weka.SMO_PolyKernel(1)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(1)_C250007
weka.PolyKernel(1)_E1.0
weka.SMO_PolyKernel(1)_C1.0
weka.SMO_PolyKernel(1)_Kweka.classifiers.functions.supportVector.PolyKernel
weka.SMO_PolyKernel(1)_L0.001
weka.SMO_PolyKernel(1)_N0
weka.SMO_PolyKernel(1)_P1.0E-12
weka.SMO_PolyKernel(1)_V-1
weka.SMO_PolyKernel(1)_W1

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

0.8772 ± 0.0229
Per class
0.7688 ± 0.0537
0.3373 ± 0.0191
0.2673 ± 0.0067
0.3798 ± 0.0012
6250
Per class
[ Oracle Corporation, 1.7.0_15, amd64, Linux, 3.5.0-27-generic ]
0.8754 ± 0.029
1.3181 ± 0.0119
0.8754 ± 0.029
Per class
0.704 ± 0.0171
0.4356 ± 0.0014
0.3452 ± 0.0097
0.7926 ± 0.0215
891.0881