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Run
10169

Run 10169

Task 57 (Supervised Classification) ionosphere 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)_C0.01
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
0.5008
Per class
KB relative information score
67.5772
Mean absolute error
0.359
Mean prior absolute error
0.4604
Number of instances
351
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.4109
Per class
Predictive accuracy
0.641
Prior entropy
0.9425
Recall
0.641
Per class
Relative absolute error
0.7796
Root mean prior squared error
0.4797
Root mean squared error
0.5991
Root relative squared error
1.249
SciMark benchmark
948.8963[570.75937279643691014.9881711071126483.23216931738307914.34946139689831761.1524117823017]