DEVELOPMENT... OpenML
Run
11609

Run 11609

Task 36 (Supervised Classification) segment 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)_G0.1
weka.SMO_RBFKernel(1)_C1.0
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
0.9692
Per class
F measure
0.8969
Per class
Kappa
0.8798
KB relative information score
789.7661
Mean absolute error
0.206
Mean prior absolute error
0.2449
Number of instances
2310
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.897
Per class
Predictive accuracy
0.897
Prior entropy
2.8074
Recall
0.897
Per class
Relative absolute error
0.8412
Root mean prior squared error
0.3499
Root mean squared error
0.3041
Root relative squared error
0.8692
SciMark benchmark
946.5309[565.57740346189041015.2555353338006484.10363182779514907.70082742804311760.017229859821]