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Let's say I have a training set {y_i,x_i}_N with y_i>0 and x_i is a vector with binary variables x_ik∈{0,1}.

Which is the best way to build a regression tree with selected variables? Should I use CvDTree or implement my own regression tree?

Let's say I have a training set {y_i,x_i}_N with y_i>0 and x_i is a vector with binary variables x_ik∈{0,1}.

Which is the best way to build a regression tree with selected variables? Should I use CvDTree or implement my own regression tree?

Let's say I have a training set {y_i,x_i}_N }_N with y_i>0 and x_i is a vector with binary variables x_ik∈{0,1}.

Which is the best way to build a regression tree with selected variables? Should I use CvDTree or implement my own regression tree?

Let's say I have a training set {y_i,x_i}_N with y_i>0 and x_i is a vector with of binary variables x_ik∈{0,1}.

Which is the best way to build a regression tree with selected variables? Should I use CvDTree or implement my own regression tree?

Let's say I have a training set {y_i,x_i}_N with y_i>0 and x_i is a vector of with binary variables x_ik∈{0,1}.

Which is the best way to build a regression tree with selected variables? Should I use CvDTree or implement my own regression tree?

Let's say I have a training set {y_i,x_i}_N with y_i>0 and x_i is a vector with of binary variables x_ik∈{0,1}.

Which is the best way to build a regression tree with selected variables? Should I use CvDTree or implement my own regression tree?