DEVELOPMENT... OpenML
Run
6896

Run 6896

Task 47 (Supervised Classification) tae Uploaded 21-05-2014 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)_G0.2
weka.SMO_RBFKernel(1)_C1.0
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
0.6452
Per class
F measure
0.5022
Per class
Kappa
0.2769
KB relative information score
37.3039
Mean absolute error
0.3782
Mean prior absolute error
0.4443
Number of instances
151
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.515
Per class
Predictive accuracy
0.5166
Prior entropy
1.5845
Recall
0.5166
Per class
Relative absolute error
0.8512
Root mean prior squared error
0.4713
Root mean squared error
0.4797
Root relative squared error
1.0177
SciMark benchmark
944.7913[559.76915123019011013.3868112175512482.7975877024999913.07556704216551754.9271701211055]