For Analytic Solver, partition data sets into $60\%$ training and $40\%$ validation and use $12345$ as the default random seed. Create $10$ weak learners when constructing the ensemble model. If the predictor variable values are in the character format, then treat the predictor variable as a categorical variable. Otherwise, treat the predictor variable as a numerical variable.

Create a boosting ensemble classification tree model using the accompanying data file $($predictor variables: x$1$ to x$4$; target: y$).$