CASE STUDY QUESTIONS(PAGE 527 OF DATA MINING FOR BUSINESS ANALYTICS)

21.3 TAYKO SOFTWARE CATALOGER

#1) DEVELOP A LOGISTIC REGRESSION MODEL FOR CLASSIFYING A CUSTOMER AS A PURCHASER OR NON PURCHASER (PARTITION TRAINING 800 RECORDS, VALIDATION 700 RECORDS AND TEST 500 RECORDS). REFER TO PROBLEM #2 IN CASE STUDY (7.5 POINTS)

Present your findings in power point format (no more than 5 slides) in terms of steps taken and results. Please submit Python code as well.

Tell a high level story of steps taken to get to the end result. Start with the framework i.e. objective, exploration, variable selection (PCA, Correlation, Exhaustive search etc). Then final results and comparison analysis of training vs. validation data vs. test.