Hi every one,

I want to build a machine learning model to do regression on continuous output given binary valued features(0,1). the dimension of my problem is around 200. which of the flowing methods seems suitable for this kind of problem ?

• SVR with different Kernels

• Regression random forest

• MARS

• Gradient boosting with regression tree

• Kernel regression (Nadya-Watson Kernel regression)

• LSR and LARS

• Stochastic gradient boosting