Decision tree is a classification algo...How can it be applied to load diabetes dataset which has DV continuous

Decision tree is a classification algorithm that can be used to predict a categorical outcome. However, it can also be used for regression tasks by treating the dependent variable as continuous. One way to apply decision tree to a diabetes dataset with a continuous dependent variable is to convert the continuous variable into a categorical variable by creating bins and then using the decision tree algorithm to predict the binned outcome. Another way would be to use a decision tree algorithm specifically designed for regression tasks such as the CART (Classification and Regression Tree) algorithm.