2012/5/24 Ian Goodfellow <[email protected]>: > Well that's the thing, coef_ and intercept_ seem wrong, given the > results of my script below. My implementation of predict based on > coef_ only agrees with predict 50% of the time. > Does anyone know if coef_ and intercept_ are just getting set wrong? > Or does predict implement a different decision function than > (X*coef_+intercept_)>0?
If X is dense then this should be, for binary classification with a linear kernel: np.dot(X, clf.coef_) - clf.intercept > 0 (if I remember correctly the sign of the intercept) Off course this formula is specific to the dense linear case. It won't work for the SVC models with kernels. -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ 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
