The provided dataset Franchises Dataset contains data collected from different $100$ franchises.The data contains the net profit $($million $$)$ for each franchise, the counter sales $($million $$),$ thedrive$-$through sales $($million $$),$ the number of customers visiting the business daily, the type ofthe franchise, and the location of the franchise.Address the following questions:a$)$ Develop a decision tree model for the net profit. Assess the accuracy of the model.b$)$ Simulate the decision tree and visualize and interpretate the impact of the descriptivefeatures.c$)$ Develop a Random Forest $($RF$)$ prediction model for the net profit.d$)$ Rationalize the selected structure of the model.e$)$ Simulate the model parameters and visualize and interpretate the impact of thedescriptive features.f$)$ What is the forecast of the net profit, if the counter sales are $500,000$ $$,$ drive$-$throughsales are $700,000$$$,$ and the franchise is a pizza store located in Richmond, using bothmodels $($Decision Tree and Random Forest$).$ Comment on the forecasted value.g$)$ What are the roles of the max$\_$feature and the n$\_$estimators parameters in the randomforest.h$)$ What are the assumptions and limitations of the models?Submit a PDF file for your answers as well as the excel sheet. Include the Python code in the