Run
1419

Run 1419

Task 239 (Supervised Classification) autos Uploaded 23-04-2014 by Jan van Rijn
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Flow

weka.SMO_PolyKernel(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.PolyKernel(1)_C250007
weka.PolyKernel(1)_E1.0
weka.SMO_PolyKernel(1)_C1.0
weka.SMO_PolyKernel(1)_Kweka.classifiers.functions.supportVector.PolyKernel
weka.SMO_PolyKernel(1)_L0.001
weka.SMO_PolyKernel(1)_N0
weka.SMO_PolyKernel(1)_P1.0E-12
weka.SMO_PolyKernel(1)_V-1
weka.SMO_PolyKernel(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
0.8615
Per class
Cross-validation details (33% Holdout set)
F measure
0.5678
Per class
Cross-validation details (33% Holdout set)
Kappa
0.479
Cross-validation details (33% Holdout set)
KB relative information score
15.5252
Cross-validation details (33% Holdout set)
Mean absolute error
0.212
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.2263
Cross-validation details (33% Holdout set)
Number of instances
67
Per class
Cross-validation details (33% Holdout set)
OS information
[ Oracle Corporation, 1.7.0_51, amd64, Linux, 3.7.10-1.28-desktop ]
Precision
0.5776
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.5821
Cross-validation details (33% Holdout set)
Prior entropy
2.3268
Cross-validation details (33% Holdout set)
Recall
0.5821
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.9368
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.3398
Cross-validation details (33% Holdout set)
Root mean squared error
0.3138
Cross-validation details (33% Holdout set)
Root relative squared error
0.9236
Cross-validation details (33% Holdout set)
SciMark benchmark
1950.3871