Run
25040

Run 25040

Task 62 (Learning Curve) anneal Uploaded 16-08-2014 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
0.8312 ± 0.0436
Per class
Build CPU time
0.1152
Build memory
293975703.5733
F measure
0.8636 ± 0.036
Per class
Kappa
0.6672 ± 0.0798
KB relative information score
-0.5362 ± 0.0348
Mean absolute error
0.2252 ± 0.0007
Mean prior absolute error
0.1343 ± 0.0012
Number of instances
8980
Per class
OS information
[Oracle Corporation, 1.7.0_55, amd64, Linux, 3.13.0-32-generic]
Precision
0.8681 ± 0.0351
Per class
Predictive accuracy
0.8738 ± 0.0277
Prior entropy
1.1915 ± 0.0248
Recall
0.8738 ± 0.0277
Per class
Relative absolute error
1.6765 ± 0.0163
Root mean prior squared error
0.2582 ± 0.0023
Root mean squared error
0.315 ± 0.0011
Root relative squared error
1.22 ± 0.0122
SciMark benchmark
775.9981[469.1340932148987973.7013819753541408.57755533778607770.7851120633991257.7921058814234]