why use split in decision tree how to split a decision tree when do you split in decision trees when using decision tree splits what is the correct approach when should the split threshold be implemented? which approach best describes predicting variable in decision tree why do we need to split a decision tree when does a decision tree split occur? which strategy is the correct one for forecasting _binary_ variables? why use decision tree splits how is splitting of data used in decision tree why are splits necessary for decision tree splitting how to use the split threshold for predicting binary variables when to use decision tree split in continuous data how to make a decision tree split when to use decision tree split for binary variable can binary variables be simulated in decision tree do decision tree splits work which strategy should be used when predicting binary variables which of the following is the correct approach for predicting binary variables?