DEVELOPMENT... OpenML
Run
13883

Run 13883

Task 49 (Supervised Classification) tic-tac-toe Uploaded 22-05-2014 by Felicia West
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Flow

weka.SMO_RBFKernel(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.RBFKernel(1)_C250007
weka.RBFKernel(1)_G0.5
weka.SMO_RBFKernel(1)_C1.0
weka.SMO_RBFKernel(1)_Kweka.classifiers.functions.supportVector.RBFKernel
weka.SMO_RBFKernel(1)_L0.001
weka.SMO_RBFKernel(1)_N0
weka.SMO_RBFKernel(1)_P1.0E-12
weka.SMO_RBFKernel(1)_V-1
weka.SMO_RBFKernel(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

Area under ROC curve
0.9841
Per class
F measure
0.9885
Per class
Kappa
0.9745
KB relative information score
932.3972
Mean absolute error
0.0115
Mean prior absolute error
0.453
Number of instances
958
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9886
Per class
Predictive accuracy
0.9885
Prior entropy
0.9312
Recall
0.9885
Per class
Relative absolute error
0.0253
Root mean prior squared error
0.4759
Root mean squared error
0.1072
Root relative squared error
0.2252
SciMark benchmark
944.5042[552.84965319085751015.52310425331484.54051677983614909.59057174132591760.0170946291457]