Document information
- University
- Politecnico di Milano
- Degree programme
- Computer Engineering
- Subject
- Data Mining and Text Mining
- Classification
- Exam · Full exam
- Content
- Exam paper only
- Original format
- Text
- Searchable text
Full exam for Data Mining and Text Mining in the Computer Engineering degree programme at Politecnico di Milano. The document covers: Politecnico di Milano Facoltà di Ingegneria dell’Informazione Data Mining and Text Mining Tecniche di Apprendimento Automatico Prof. Pier Luca Lanzi & Ing. Daniele Loiacono June 29, 2015 NAME MATRICOLA Solve the following problems and write the answer inside the problem box.
Full exam for Data Mining and Text Mining in the Computer Engineering degree programme at Politecnico di Milano. The document covers: Politecnico di Milano Facoltà di Ingegneria dell’Informazione Data Mining and Text Mining Tecniche di Apprendimento Automatico Prof. Pier Luca Lanzi & Ing. Daniele Loiacono June 29, 2015 NAME MATRICOLA Solve the following problems and write the answer inside the problem box.
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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 June 29, 2015 NAME MATRICOLA Solve the following problems and write the answer inside the problem box. Answers must be clearly written. Pencils are not allowed. The midterm consists of 3 sheets of paper. It must be returned with all the 3 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. All the answers must be adequately motivated. Grades 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 estimated accuracy of k-nearest neighbor using k = 1, Euclidean distance, and a tenfold cross validation on the following dataset where X and Y are the attributes and C is the class. Solution must be adequately commented. X Y C 1 2 7 1 2 10 3 1 3 1 7 0 4 5 8 0 5 10 1 0 6 3 5 0 7 3 6 0 8 2 2 1 9 4 9 0 10 6 9 1 Problem 1. (continued) Problem 2. What is the Bag of Words model and how does it relate to the Vector Space Model? Problem 3 (5 points – only for students who did not do the course project). You work at “I Know Data”, a leader in Big Data. You manage two teams (A and B), which report their findings every week. Team A is working on a data set…
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