Hi, > I have found scikit-learn (version 0.8.1) recently and I found it useful to > classify my data using SVM. I've modify given example: plot_custom_kernel.py > to use a non-linear SVC with RBF kernel and I have one question. I would > like to find a function of line separating two different areas. I'm new to > this tool and I'm not familiar with python either so I would be grateful for > any advice.
are you looking the analytic formula for the decision function? maybe this example : http://scikit-learn.sourceforge.net/auto_examples/svm/plot_svm_nonlinear.html can help. > And also I'm going to publish these results, what reference for scikit-learn > should I give? F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, E. Duchesnay, 'Scikit-learn: Machine learning in Python', accepted for publication in JMLR. Alex ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity and more. Splunk takes this data and makes sense of it. Business sense. IT sense. Common sense. http://p.sf.net/sfu/splunk-d2dcopy1 _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
