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From Srivatsan Ramanujam <>
Subject Elastic net regression - log likelihood
Date Tue, 08 Dec 2015 17:55:59 GMT
Hi guys,

I was looking at this:
and noticed that the log_likelihood is defined as the *negative* value of
the L(w) defined in the equation.

Any reason why you've included the negative sign?

I was a little confused as i assumed the log_likelihood reported was
actually the value of L(w) (the lower the better since we are minimizing
L(w) for w), but then noticed while doing a grid-search on the alpha and
lambdas my best performing models had log_likelihood values < 0 but close
to zero. The values which had higher magnitude (negative sign again)
performed poorly. Just wondering what's the need to multiply the
log_likelihood by -1, why not report raw values and let user pick the w
with lowest L(w) ?

Please clarify if i have misunderstood.


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