DEVELOPMENT... OpenML
Run
11893

Run 11893

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)_G1.0
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
0.6548
Per class
F measure
0.7118
Per class
Kappa
0.3531
KB relative information score
314.372
Mean absolute error
0.2578
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
0.7501
Per class
Predictive accuracy
0.7422
Prior entropy
0.9335
Recall
0.7422
Per class
Relative absolute error
0.5673
Root mean prior squared error
0.4766
Root mean squared error
0.5078
Root relative squared error
1.0653
SciMark benchmark
950.0279[565.57735973810441015.5230404536866483.88543266528814916.58736979803611768.5664600912808]