DEVELOPMENT... OpenML
Run
8642

Run 8642

Task 30 (Supervised Classification) page-blocks 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)_G100.0
weka.SMO_RBFKernel(1)_C0.1
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
0.6624
Per class
F measure
0.9017
Per class
Kappa
0.4298
KB relative information score
-17134.6242
Mean absolute error
0.2447
Mean prior absolute error
0.0762
Number of instances
5473
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8992
Per class
Predictive accuracy
0.9244
Prior entropy
0.6391
Recall
0.9244
Per class
Relative absolute error
3.213
Root mean prior squared error
0.1949
Root mean squared error
0.3236
Root relative squared error
1.6605
SciMark benchmark
944.6285[561.20997989739871016.0585376856843478.28140966761225909.27509318503251758.3172656914378]