I ran: >> model = SVR(kernel="poly", degree=2) but the % Error of the prediction is worse than using simple Ordinary Least Squares using: >> linear_model.LinearRegression()
It's also much slower. I changed the degree to 4 to see if the results of the prediction got any better, but it's taking too long to run. I only have 50 cases and 8 features for each case, but it's been over 2-hours and it's still running this fit: model = SVR(kernel="poly", degree=4) model.fit(X,y) I'm going to manually stop it now by closing the python window. Am I doing something wrong? Zach On 08/08/2012 19:44, Mathieu Blondel wrote: > R or ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
