Hi guys,
I was looking at this:
http://doc.madlib.net/latest/group__grp__elasticnet.html
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 gridsearch 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.
Thanks
Vatsan
