Run
25250

Run 25250

Task 98 (Learning Curve) sonar 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
0.7786 ± 0.0938
Per class
Build CPU time
0.0081
Build memory
5346699219.472
F measure
0.7804 ± 0.0934
Per class
Kappa
0.5585 ± 0.1865
KB relative information score
0.5587 ± 0.1856
Mean absolute error
0.2192 ± 0.0922
Mean prior absolute error
0.4978 ± 0.0015
Number of instances
2080
Per class
OS information
[Oracle Corporation, 1.7.0_55, amd64, Linux, 3.8.0-44-generic]
Precision
0.7806 ± 0.0929
Per class
Predictive accuracy
0.7808 ± 0.0922
Prior entropy
0.9967 ± 0.0043
Recall
0.7808 ± 0.0922
Per class
Relative absolute error
0.4404 ± 0.1853
Root mean prior squared error
0.4989 ± 0.0015
Root mean squared error
0.4682 ± 0.1098
Root relative squared error
0.9386 ± 0.2202
SciMark benchmark
1157.7312[691.3359645982486952.9946411086055533.4037843495669949.45304292035022661.4687358891606]