It seems that training data set is way too small. What are the errors on performance estimates?
-- On Mon, Jul 11, 2011 at 2:26 PM, Weihua Zhu <w...@adconion.com> wrote: > Target class is if a user click an ad(advertisement), buy through an ad, or > not; so 3 classes. > Feature A s about the Advertisement itself; > Feature B is about the user's behaviors; > Currently im only using feature A and B. > Total training data is 250 for each class; > > thanks.. > > > ________________________________________ > From: Ted Dunning [ted.dunn...@gmail.com] > Sent: Monday, July 11, 2011 2:15 PM > To: user@mahout.apache.org > Subject: Re: combination of features worsen the performance > > Can you say a little bit about the data? > > What are features A and B? What kind of data do they represent? > > How many other features are there? > > What is the target variable? How many possible values does it have? > > How much training data do you have? > > What sort of training are you doing? > > > > On Mon, Jul 11, 2011 at 2:08 PM, Weihua Zhu <w...@adconion.com> wrote: > >> Hi, Dear all, >> >> I am using mahout logistic regression for classification; interestingly, >> for feature A, B, individually each has satisfactory performances, say 65%, >> 80%, but when i combine them together(using encoder), the performance is >> like 72%. Shouldn't the performance be better? Any thoughts? Thanks a lot, >> >> >> -wz. >> > -- ksh:
