The algorithm of decision tree models works by repeatedly partitioning the data into multiple sub-spaces, so that the outcomes in each final sub-space is as homogeneous as possible. This approach is technically called recursive partitioning. The produced result consists of a set of rules used for predicting the outcome variable, which can be either: a continuous variable, for regression trees a categorical variable, for classification trees The decision rules generated by the CART predictive model are generally visualized as a binary tree.

Have made analysis on Super store data . We compare the profits and sales based on category and discount offered on pruducts

Visualizing using various types of plots makes it easier to understand the data

Various types of scatter plots covered. Do try to understand the code and the logic behind that

Amazon stock prediction with accurate forecasting

Have predicted stocks and monthly returns of amazon purposely have named the file as MSFT