Visibility: public Uploaded 04-04-2014 by Jan van Rijn Weka_3.7.10 1833 runs
0 likes downloaded by 3 people 0 issues 0 downvotes , 3 total downloads
  • Verified_Learning_Curve,Verified_Supervised_Classification
Issue #Downvotes for this reason By

Loading wiki
Help us complete this description Edit
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.


Kweka.RBFKernel(1)The Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel)


CThe complexity constant C. (default 1)default: 1.0
DIf set, classifier is run in debug mode and may output additional info to the console
EThe Exponent to use. (default: 1.0)
KThe Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel)default: weka.classifiers.functions.supportVector.RBFKernel
LThe tolerance parameter. (default 1.0e-3)default: 0.001
MFit logistic models to SVM outputs.
NWhether to 0=normalize/1=standardize/2=neither. (default 0=normalize)default: 0
PThe epsilon for round-off error. (default 1.0e-12)default: 1.0E-12
VThe number of folds for the internal cross-validation. (default -1, use training data)default: -1
WThe random number seed. (default 1)default: 1
no-checksTurns off all checks - use with caution! Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a nominal class. Turning them off also means that no header information will be stored if the machine is linear. Finally, it also assumes that no instance has a weight equal to 0. (default: checks on)


List all runs
Rendering chart
Rendering table