can decision trees handle continuous variables what kind of features does decision trees handle why do decision trees have discrete data and categorical data can you use dummy variables in decision tree which model is better categorical or continuous which of the following is better to use a decision tree or categorical feature? can decision trees detect categorical variable how to predict continuous data which model handles both continuous and categorical variables which type of data does a decision tree handle? why decision tree splits used when categorical variable what is the difference between categorical and continuous features in p-splits? quizlet which is a better method of decision tree splitting are decision trees discrete can decision tree split a continuous variable what is decision tree data what kind of data to use in a decision tree how should decision trees be implemented for categorical variable data? what kind of data can a decision tree predict is decision tree discretized?