Run
682

Run 682

Task 86 (Learning Curve) colic Uploaded 07-04-2014 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

0.8143 ± 0.0613
Per class
0.8289 ± 0.0536
Per class
0.6319 ± 0.1157
0.6228 ± 0.1144
0.1707 ± 0.0519
0.4662 ± 0.0029
3680
Per class
[ Sun Microsystems Inc., 1.6.0_30, amd64, Linux, 2.6.32-358.6.2.el6.x86_64 ]
0.8286 ± 0.0522
Per class
0.8293 ± 0.0519
0.9503 ± 0.0087
0.8293 ± 0.0519
Per class
0.3661 ± 0.1111
0.4827 ± 0.0031
0.4131 ± 0.0641
0.8558 ± 0.1326
804.0821