DEVELOPMENT... OpenML
Run
13160

Run 13160

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)_G10.0
weka.SMO_RBFKernel(1)_C100.0
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
0.6686
Per class
F measure
0.6991
Per class
Kappa
0.3375
KB relative information score
238.8156
Mean absolute error
0.3008
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
0.699
Per class
Predictive accuracy
0.6992
Prior entropy
0.9335
Recall
0.6992
Per class
Relative absolute error
0.6618
Root mean prior squared error
0.4766
Root mean squared error
0.5484
Root relative squared error
1.1506
SciMark benchmark
946.2764[561.57136831653141016.0585376856843489.84574223453643903.32186243855711760.5845701777503]