DEVELOPMENT... OpenML
Run
14343

Run 14343

Task 55 (Supervised Classification) vote Uploaded 22-05-2014 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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)_C100.0
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
0.9144
Per class
F measure
0.9278
Per class
Kappa
0.8465
KB relative information score
367.9905
Mean absolute error
0.0713
Mean prior absolute error
0.4742
Number of instances
435
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9308
Per class
Predictive accuracy
0.9287
Prior entropy
0.9627
Recall
0.9287
Per class
Relative absolute error
0.1503
Root mean prior squared error
0.4869
Root mean squared error
0.267
Root relative squared error
0.5483
SciMark benchmark
946.116[566.86401039670471016.0585376856843483.6674820550281912.43998791392861751.5501218345944]