DEVELOPMENT... OpenML
Run
12710

Run 12710

Task 30 (Supervised Classification) page-blocks Uploaded 22-05-2014 by Felicia West
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Flow

weka.SMO_RBFKernel(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.RBFKernel(1)_C250007
weka.RBFKernel(1)_G1.0
weka.SMO_RBFKernel(1)_C0.01
weka.SMO_RBFKernel(1)_Kweka.classifiers.functions.supportVector.RBFKernel
weka.SMO_RBFKernel(1)_L0.001
weka.SMO_RBFKernel(1)_N0
weka.SMO_RBFKernel(1)_P1.0E-12
weka.SMO_RBFKernel(1)_V-1
weka.SMO_RBFKernel(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.

19 Evaluation measures

Area under ROC curve
0.5
Per class
F measure
0.8493
Per class
KB relative information score
-17411.3794
Mean absolute error
0.2468
Mean prior absolute error
0.0762
Number of instances
5473
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8058
Per class
Predictive accuracy
0.8977
Prior entropy
0.6391
Recall
0.8977
Per class
Relative absolute error
3.2412
Root mean prior squared error
0.1949
Root mean squared error
0.3269
Root relative squared error
1.6775
SciMark benchmark
948.3313[566.86405431965431015.2555353338006483.667533998868909.59057174132591766.2785639901995]