DEVELOPMENT... OpenML
Run
196255

Run 196255

Task 4345 (Supervised Classification) disclosure_x_bias Uploaded 26-02-2015 by Felicia West
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Flow

weka.SMO_PolyKernel(10)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(8)_E1.0
weka.PolyKernel(8)_C250007
weka.SMO_PolyKernel(10)_C1.0
weka.SMO_PolyKernel(10)_N0
weka.SMO_PolyKernel(10)_L0.001
weka.SMO_PolyKernel(10)_P1.0E-12
weka.SMO_PolyKernel(10)_V-1
weka.SMO_PolyKernel(10)_W1
weka.SMO_PolyKernel(10)_Kweka.classifiers.functions.supportVector.PolyKernel

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.

22 Evaluation measures

Area under ROC curve
0.5616
Per class
F measure
0.5622
Per class
Kappa
0.1239
KB relative information score
845.1442
Mean absolute error
0.435
Mean prior absolute error
0.4991
Number of instances
6620
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.5636
Per class
Predictive accuracy
0.565
Prior entropy
0.9987
Recall
0.565
Per class
Relative absolute error
0.8716
Root mean prior squared error
0.4996
Root mean squared error
0.6596
Root relative squared error
1.3203
SciMark benchmark
1318.5526
UserCPU time millis
10
UserCPU time millis training
10