Need Help In My Assignment

Predicting credit downgrades Firms’ credit rating is one of the key parameters in investment, financial and operational decision making. Your company asked you to assist in the company’s risk evaluation using a dataset of firms that the company in may consider for investment. The dataset includes financial variables, online activity data (i.e. Google Trends and Wikipedia stats), the current rating of the firm (marked as “RatingRank”), and whether this rating reflects a downgrade from the last rating (marked as “Downgrade” in the dataset). Your training dataset (“events_training.csv”) include over 2700 records of previous events. Your goal is to estimate if the firm will be downgraded in a new dataset (“events_test.csv”) with 400 records, where you have all the attributes but not the RatingRank or the Downgrade values (these measures were set to 1 for all these new records but don’t reflect the actual Downgrade value for the 400 records).

a. Describe the data preparation, the models you created (provide screenshots), and the different input parameters. Run different prediction models in RapidMiner with different variables.

b. Choose the best model and apply it on the new records events_test.csv file. Save the results as a csv file