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Run
22752

Run 22752

Task 2065 (Supervised Classification) primary-tumor Uploaded 22-06-2014 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
0.4732
Per class
F measure
0.0984
Per class
KB relative information score
7.8616
Mean absolute error
0.0844
Mean prior absolute error
0.0812
Number of instances
339
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.0614
Per class
Predictive accuracy
0.2478
Prior entropy
3.7542
Recall
0.2478
Per class
Relative absolute error
1.0389
Root mean prior squared error
0.2011
Root mean squared error
0.2043
Root relative squared error
1.016
SciMark benchmark
940.549[549.54020994765531009.6699252256896485.41676123331996904.880888052811753.2370197795062]