Sales Order Delivery Days Prediction Using ML Decision Tree Regression
The decision trees are used to fit a sine curve with additional noisy observation. As a result, it learns local linear regressions approximating the sine curve.
We can see that if the maximum depth of the tree (controlled by the max_depth parameter) is set too high, the decision trees learn too fine details of the training data and learn from the noise, i.e. they overfit.
We can create a model Scikit Learn Decision Tree Regressor to check how it performs on Delivery Days Prediction. We have seen in our previous blog posts Customer Price Prediction on Machine Learning Scikit Learn Linear Regression and Random Forest models.
Let’s start and see how the decision tree predicts “Delivery days data”.
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