DEVELOPMENT... OpenML
Run
13984

Run 13984

Task 22 (Supervised Classification) mfeat-zernike 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)_C10.0
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
0.9679
Per class
F measure
0.8365
Per class
Kappa
0.8211
KB relative information score
577.252
Mean absolute error
0.161
Mean prior absolute error
0.18
Number of instances
2000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8344
Per class
Predictive accuracy
0.839
Prior entropy
3.3219
Recall
0.839
Per class
Relative absolute error
0.8946
Root mean prior squared error
0.3
Root mean squared error
0.2738
Root relative squared error
0.9126
SciMark benchmark
947.9097[560.48863959327881015.7906865781697484.10363182779514911.17132945493631767.9939646936223]

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