Hi,
Right now LogisticGradient implements both binary and multi-class in the
same class using an if-else statement which is a bit convoluted.
For Generalized matrix factorization, if the data has distinct ratings I
want to use LeastSquareGradient (regression has given best results to date)
but
I did the benchmark when I used the if-else statement to switch the
binary multinomial logistic loss and gradient, and there is no
performance hit at all. However, I'm refactoring the LogisticGradient
code so the addBias and scaling can be done in LogisticGradient
instead of the input dataset to
Cool...Thanks...It will be great if they move in two code paths just for
the sake of code clean-up
On Wed, Mar 25, 2015 at 2:37 PM, DB Tsai dbt...@dbtsai.com wrote:
I did the benchmark when I used the if-else statement to switch the
binary multinomial logistic loss and gradient, and there is
