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 if the data has binary labels 0/1 based on domain knowledge (implicit for example, visits no-visits) I want to use a LogisticGradient without any overhead for multi-class if-else... I can compare the performance of LeastSquareGradient and multi-class LogisticGradient on the recommendation metrics but it will be great if we can separate binary and multi-class in Separate classes....MultiClassLogistic can extend BinaryLogistic but mixing them in the same class is an overhead for users (like me) who wants to use BinaryLogistic for his application.. Thanks. Deb
