DEVELOPMENT... OpenML
Run
196340

Run 196340

Task 4433 (Supervised Classification) sleuth_ex2015 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
0.6392
Per class
F measure
0.6439
Per class
Kappa
0.2875
KB relative information score
184.1322
Mean absolute error
0.3417
Mean prior absolute error
0.4952
Number of instances
600
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.6639
Per class
Predictive accuracy
0.6583
Prior entropy
0.9932
Recall
0.6583
Per class
Relative absolute error
0.69
Root mean prior squared error
0.4975
Root mean squared error
0.5845
Root relative squared error
1.1749
SciMark benchmark
1318.5526
UserCPU time millis
10
UserCPU time millis training
10