Hello Ted, Thanks for the reply. But I am not able to understand what is the point of *subtracting the max value from every array element*. Here they are using *softmax regression* instead of standard logistic regression. So how does subtracting max value solves the problem?
Thanks Namit On Fri, May 23, 2014 at 6:18 PM, Ted Dunning <ted.dunn...@gmail.com> wrote: > exp(40) > 10^17 > > Thus, if x >= 1, for x + exp(-40) all significant bits of the exponential > are lost and the result is identical to just saying x. Likewise for x <=1, > for 1+exp(40), the addition of 1 has no effect. > > The logistic function [1] is defined as f(x) = 1 / (1 + exp(-x)), thus when > using double precision floating point where x >= 40, f(x) = 1 and where x > <= -40, f(x) = 0. > > > [1] https://en.wikipedia.org/wiki/Logistic_function > > > > On Fri, May 23, 2014 at 4:23 AM, namit maheshwari < > namitmaheshwa...@gmail.com> wrote: > > > Hello Everyone, > > > > In mahout's *AbstractOnlineLogisticRegression *class the *public static > > Vector link(Vector v)* > > function checks the *max* value against 40. > > > > Could anyone please explain the significance of 40 in context of Logistic > > Regression? > > > > Thanks > > Namit > > >
