Run
25223

Run 25223

Task 71 (Learning Curve) mfeat-factors 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

0.9937 ± 0.0031
Per class
0.2845
4431055165.3673
0.9746 ± 0.0091
Per class
0.9718 ± 0.0101
0.298 ± 0.0014
0.1603 ± 0.0001
0.18
20000
Per class
[Oracle Corporation, 1.7.0_55, amd64, Linux, 3.8.0-44-generic]
0.9747 ± 0.0087
Per class
0.9746 ± 0.0091
3.3219
0.9746 ± 0.0091
Per class
0.8903 ± 0.0007
0.3
0.2723 ± 0.0002
0.9076 ± 0.0007
1154.4743[687.7920468521236978.646534145704531.2923664726713947.73679293915542626.9039650573236]