On Wed, Mar 22, 2017 at 06:39:16AM +0530, Sudhanshu Ranjan wrote: > Advantage : We will be able to cover all the train functions which take > first input as TrainingData and second input as TrainingLabels. > Disadvantage : There will be a number of overloaded functions (3-4 ) for > Evaluate. (for example in AdaBoost the Train function accepts 3 extra > parameters whereas Logistic Regression has a train function with no extra > parameter.)
Hi Sudhanshu, I appreciate the thought you have put into this so far. My only comment at this point is that I don't see a need to overload several functions for when the learners have different numbers of parameters. You could use variadic templates to solve this problem. Thanks, Ryan -- Ryan Curtin | "I was misinformed." [email protected] | - Rick Blaine _______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
