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Politecnico di Milano Facoltà di Ingegneria dell’Informazione Data Mining and Text Mining Tecniche di Apprendimento Automatico Prof. Pier Luca Lanzi & Ing. Daniele Loiacono May 24, 2013 NAME MATRICOLA Solve the following problems and write the answer inside the problem box. Answers must be clearly written. Pencils are not allowed. The final consists of 5 sheets of paper. It must be returned with all the 5 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. Grades Data Mining and Text Mining Problems 1, 2 (each assigning 7 points) Tecniche di Apprendimento Automatico per Applicazioni di Data Mining Problems 1, 2, 3, and 4 (each assigning 8 points) The image cannot be displayed. Your computer may not have enough memory to open the image, or the image may have been corrupted. Restart your computer, and then open the file again. If the red x still appears, you may have to delete the image and then insert it again. Problem 1. Compute the best splitting attribute using the information gain for the following data set in which attribute D is the class. How would the procedure change if Gini index was used instead? Do you foresee any possible advantage of Gini index with respect to information gain in this specific case? A B C D 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 2 2 1 2 2 4 1 3 2 5 1 3 2 5 1 2 1 1 0 2 1 1 0 3 1 1 0 3 1 3 0 4 3 3 0 4 3 4 0 4 2 6 0 4 2 6 0 Problem 2. Briefly discuss the differences between sequential covering algorithms, decision trees…