Hi All I am building a logistic regression for matching the person data lets say two person object is given with their attribute we need to find the score. that means at side you have 10 millions records and other side we have 1 record , we need to tell which one match with highest score among 1 million.
I am strong the score of similarity algos in dense matrix and considering this as features. will apply many similarity alogs on one attributes. Should i use sparse or dense? what happen in dense when score is null or when some of the attribute is missing? is there any support for regularized logistic regression ?currently i am using LogisticRegressionWithSGD. Regards jeetendra
