DEVELOPMENT... OpenML
Run
11184

Run 11184

Task 36 (Supervised Classification) segment Uploaded 22-05-2014 by Felicia West
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Flow

weka.SMO_PolyKernel(1)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(1)_C250007
weka.PolyKernel(1)_E3.0
weka.SMO_PolyKernel(1)_C0.01
weka.SMO_PolyKernel(1)_Kweka.classifiers.functions.supportVector.PolyKernel
weka.SMO_PolyKernel(1)_L0.001
weka.SMO_PolyKernel(1)_N0
weka.SMO_PolyKernel(1)_P1.0E-12
weka.SMO_PolyKernel(1)_V-1
weka.SMO_PolyKernel(1)_W1

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

Area under ROC curve
0.9603
Per class
F measure
0.8781
Per class
Kappa
0.8591
KB relative information score
780.4687
Mean absolute error
0.2065
Mean prior absolute error
0.2449
Number of instances
2310
Per class
Precision
0.8797
Per class
Predictive accuracy
0.8792
Prior entropy
2.8074
Recall
0.8792
Per class
Relative absolute error
0.8434
Root mean prior squared error
0.3499
Root mean squared error
0.3052
Root relative squared error
0.8722