Thanks, I thought of that, but that doesn't seem to be the right explanation either For one, in the output I see the equation like TargetVariable ~ -0.001*InterceptTerm + - 0.0006*predictor1 + -0.0004*predictor2 .... Also if I look at the say predictor1, the co-efficient in R is 1.02 and for predictor2 is 0.48 whereas in Mahout, I get -0.00063 for predictor1 and -0.00042 for predictor2. Now if these values are logs of what I am looking for, e^ -0.00063 is 0.999937 and e^ -0.00042 is 0.99958, so the difference is marginal, whereas R co-efficients indicate predictor1 has much higher weightage compared to predictor2 which is what I would expect. Any other thoughts, ideas? Thanks Prabhu -----Original Message----- From: Jake Mannix [mailto:jake.mannix@gmail.com] Sent: 31 January 2013 04:54 To: user@mahout.apache.org Subject: Re: Logistic Regression in Mahout Looks like you're looking at weights which are logs of the weights you think you want. On Wed, Jan 30, 2013 at 4:12 AM, Prabhu wrote: > Hi all, > > I am trying to use Mahout to run logistic regression analysis on > some data. The data is about 7 Million rows, with about 20 predictor > variables (all of them numeric). The target variable is Boolean - 0 or 1. > > I run a logistic regression with this data on R and I get good > co-efficients which makes sense. But when I run a logistic regression > on the exact same data using Mahout, I get co-efficients that don't > make sense. For a start, all co-efficients are negative. The > interesting thing is that the co-efficient (from R) for the most > important variable (with highest > co-efficient) has the least negative value in Mahout. Can someone > please help me understand what the cause of the problem is? > > > > Thanks > > Prabhu > > > > -- -jake