Run
1840

Run 1840

Task 2097 (Learning Curve) satimage Uploaded 23-04-2014 by Jan van Rijn
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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.

19 Evaluation measures

0.9598 ± 0.0027
Per class
0.8646 ± 0.0097
Per class
0.837 ± 0.0111
0.3405 ± 0.0011
0.2258 ± 0.0002
0.2701 ± 0
6430
Per class
[ Oracle Corporation, 1.7.0_15, amd64, Linux, 3.5.0-27-generic ]
0.8628 ± 0.0097
Per class
0.8684 ± 0.0089
2.4834 ± 0.0009
0.8684 ± 0.0089
Per class
0.836 ± 0.0008
0.3675 ± 0
0.3155 ± 0.0004
0.8585 ± 0.0009
838.0153