DEVELOPMENT... OpenML
Run
12629

Run 12629

Task 37 (Supervised Classification) diabetes 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)_G0.1
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
0.7028
Per class
F measure
0.754
Per class
Kappa
0.4457
KB relative information score
364.7429
Mean absolute error
0.2292
Mean prior absolute error
0.4545
Number of instances
768
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7725
Per class
Predictive accuracy
0.7708
Prior entropy
0.9335
Recall
0.7708
Per class
Relative absolute error
0.5042
Root mean prior squared error
0.4766
Root mean squared error
0.4787
Root relative squared error
1.0043
SciMark benchmark
951.1096[571.32018311252821016.3265300883295484.9782432137119911.48820099582031771.4347814845607]