DEVELOPMENT... OpenML
Run
10470

Run 10470

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)_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
0.5
Per class
F measure
0.5134
Per class
KB relative information score
154.1008
Mean absolute error
0.349
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
0.4239
Per class
Predictive accuracy
0.651
Prior entropy
0.9335
Recall
0.651
Per class
Relative absolute error
0.7678
Root mean prior squared error
0.4766
Root mean squared error
0.5907
Root relative squared error
1.2394
SciMark benchmark
947.9844[572.6331706551471015.7907504114269483.6674820550281914.03067367712611753.799996626104]