2013/11/26 Abhi <[email protected]>: > How can we normalize and compare probabilities from different classifier > models in scikit?
Why do you want to do that? To be more specific, how do you quantify success of your task? By definition, probabilities are "normalized" in the sense that the are guaranteed to live in the [0-1] range. However the classifier models can be predict arbitrarily bad probabilities. For instance a badly trained or badly parameterized binary classifier could predict 0 proba for the positive class 100% of the time. -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ Shape the Mobile Experience: Free Subscription Software experts and developers: Be at the forefront of tech innovation. Intel(R) Software Adrenaline delivers strategic insight and game-changing conversations that shape the rapidly evolving mobile landscape. Sign up now. http://pubads.g.doubleclick.net/gampad/clk?id=63431311&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
