Answer this using sas via for learner.

Data Analysis Assignment $2 A business intelligent consulting firm would like to allocate sales force resource across online leads based on conversion rating. The firms has a website demonstrating its research white papers and consulting services in the fields of Business Intelligence (BI), Analytics, Customer Intelligence (CI), High Performance Analytics, Information Management, and Visual Analytics. Thus, this website allows the data scientist team to collect data about visitors' interests (based on the webpages visitors viewed), traffic sources (including direct visit, organic search, paid search, blog post, guest post(affiliate), online display ads, and social media), browsing behaviors on the website (such as active time, pages visited, and the number of white papers downloaded). Using this dataset, the data scientist team builds a predictive model for conversion rating. Please analyze the data and answer the following questions. (1) Use a decision tree, random forest, and gradient boosting model to build a model to predict conversion rating (dependent variable: Goal_SiteConversion_Rating). Which model performs best in terms of Average Squared Error? What major parameters did you use in the winner model? (Copy and paste the "Model Comparison" table and the "Output" table. Adjust the following major parameters to achieve a better performance. Decision tree: maximum depth, minimum leaf size, and pruning options; Random Forest: the number of trees, in-bag sample proportion, number of inputs to consider per split; Gradient boosting: the number of trees, learning rate, L1/L2 regularization). (2) Based on the winner model, what's the most important variable that affect the predicted conversion rating. How does it affect the predicted conversion rating? (Use the Model Variable Importance table and the PD plot of the most important variable). (3) Based on the winner model, which sources of traffic brings visitors with higher conversion ratings? (Use the PD plot of Trafic_source and interpret). (4) Based on the winner model, customers with which type of interest are more likely to be converted? (Use all interest-related PO plot and interpret) (5) Based on the predictive insights derived from the model, what marketing suggestions would you make to the website? Data Name: DISCOVER360DATA Where to find the data: Under the "Available" tab, search for "DIscovER3600ATA" Note: 1) Change the role of variable according to Column 1; 2) Change the maximum variable of variables under the PD/ICE options to 10