Run
25237

Run 25237

Task 82 (Learning Curve) cmc Uploaded 17-08-2014 by Jan van Rijn
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Flow

weka.SMO_PolyKernel(6)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(4)_C250007
weka.PolyKernel(4)_E1.0
weka.SMO_PolyKernel(6)_C1.0
weka.SMO_PolyKernel(6)_Kweka.classifiers.functions.supportVector.PolyKernel
weka.SMO_PolyKernel(6)_L0.001
weka.SMO_PolyKernel(6)_N0
weka.SMO_PolyKernel(6)_P1.0E-12
weka.SMO_PolyKernel(6)_V-1
weka.SMO_PolyKernel(6)_W1

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

21 Evaluation measures

Area under ROC curve
0.6366 ± 0.0263
Per class
Build CPU time
0.0908
Build memory
4497417152.032
F measure
0.4859 ± 0.0374
Per class
Kappa
0.2034 ± 0.0579
KB relative information score
0.2188 ± 0.0282
Mean absolute error
0.3774 ± 0.0113
Mean prior absolute error
0.4308 ± 0.0004
Number of instances
14730
Per class
OS information
[Oracle Corporation, 1.7.0_55, amd64, Linux, 3.8.0-44-generic]
Precision
0.4856 ± 0.0372
Per class
Predictive accuracy
0.4864 ± 0.0379
Prior entropy
1.539 ± 0.0028
Recall
0.4864 ± 0.0379
Per class
Relative absolute error
0.8761 ± 0.0263
Root mean prior squared error
0.4641 ± 0.0004
Root mean squared error
0.4755 ± 0.0119
Root relative squared error
1.0245 ± 0.0256
SciMark benchmark
1174.0251[691.3359645982486984.8990916482671541.6099786524277940.5955620236442711.684954737561]