Esame completo di Data Mining and Text Mining per il corso di Computer Engineering presso Politecnico di Milano. Materiale proveniente dall’archivio storico Studwiz e classificato per la consultazione online.
Esame completo di Data Mining and Text Mining per il corso di Computer Engineering presso Politecnico di Milano. Materiale proveniente dall’archivio storico Studwiz e classificato per la consultazione online.
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Politecnico di Milano School of Industrial and Information Engineering Data Mining and Text Mining June 25, 2018 NAME CODICE PERSONA/ID GENERAL INSTRUCTIONS • Answers must be clearly written inside the answer box designated for each problem. • All the answers must be adequately motivated. • Pencils are not allowed. The exam consists of 6 sheets of paper. It must be returned with all the 6 sheets. No any other sheet can be added. No sheet can be removed. • This is a closed-book/closed-notes exam. • Only non-programmable calculators are allowed. • Notes/books/mobile phones are not allowed. • If you are caught using forbidden material, the exam will immediately end and an RP grade will be recorded; then, your Data Mining exam will consist of an oral examination from then on. SCORING • A problem left unsolved will amount to zero points. • A completely wrong solution will amount to -3 points UIC STUDENTS HAVE 1:00h TO SOLVE PROBLEMS 3 AND 4 STUDENTS WHO DID THE COURSE PROJECT HAVE 1:40h TO SOLVE PROBLEMS 1, 2, 3, AND 4 ALL THE OTHER STUDENTS HAVE 2:20h TO SOLVE ALL THE SIX PROBLEMS COURSE PROJECT SCORE FINAL TIME GRADES 1 2 3 4 5 6 Problem 1 (6 points). Consider a data set that has been imported into a pandas dataframe called data and the output of the describe commands below: Question #1 What would be the best way to check the distribution of attribute values for nominal attributes? Answer Question #2 What would be the best way to check the distribution of attribute values for numerical attributes? Answer Question #3 Are there any attributes you would apply imputation to? If yes, which ones? If not, explain why. Answer Problem 1 (continued). Question #4 Are there any attributes you would eliminate? If yes, which ones? If not, explain why. Answer Question #5 Suppose you…
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