DEVELOPMENT...
Issue | #Downvotes for this reason | By |
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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)_C | 250007 |
weka.PolyKernel(1)_E | 1.0 |
weka.SMO_PolyKernel(1)_C | 10.0 |
weka.SMO_PolyKernel(1)_K | weka.classifiers.functions.supportVector.PolyKernel |
weka.SMO_PolyKernel(1)_L | 0.001 |
weka.SMO_PolyKernel(1)_N | 0 |
weka.SMO_PolyKernel(1)_P | 1.0E-12 |
weka.SMO_PolyKernel(1)_V | -1 |
weka.SMO_PolyKernel(1)_W | 1 |
0.9861 Per class |
0.8507 Per class |
0.8443 |
4140.9678 |
0.0711 |
0.074 |
20000 Per class |
0.8529 Per class |
0.8503 |
4.6998 |
0.8503 Per class |
0.9614 |
0.1923 |
0.186 |
0.9671 |