DEVELOPMENT... OpenML
Run
20900

Run 20900

Task 2075 (Supervised Classification) abalone Uploaded 18-06-2014 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)_G5.0
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
0.7284
Per class
F measure
0.2358
Per class
Kappa
0.1564
KB relative information score
236.7097
Mean absolute error
0.0646
Mean prior absolute error
0.0618
Number of instances
4177
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.2349
Per class
Predictive accuracy
0.2712
Prior entropy
3.6268
Recall
0.2712
Per class
Relative absolute error
1.0461
Root mean prior squared error
0.1757
Root mean squared error
0.1782
Root relative squared error
1.0144
SciMark benchmark
938.0105[552.49939948384381001.5358540365828483.0147548568529904.2565878661748.7459163532728]