Informazioni sul documento
- Università
- Politecnico di Milano
- Corso di laurea
- Computer Engineering
- Materia
- Data Mining and Text Mining
- Classificazione
- Esame · Esame completo
- Contenuto
- Testo d’esame
- Formato originale
- Testo
- Testo ricercabile
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.
Qualità dell’importazione: il testo è stato estratto direttamente dal documento originale.
Passaggi rappresentativi riconosciuti nelle diverse parti del materiale. Il testo completo resta presente nella pagina per la ricerca, mentre l’anteprima compatta rende più semplice la lettura.
Politecnico di Milano School of Industrial and Information Engineering Data Mining and Text Mining June 26, 2017 NAME CODICE PERSONA/ID GENERAL INSTRUCTIONS • You have 1:10h (one hour and ten minutes) to complete the test. • Answers must be clearly written inside the problem box. All the answers must be adequately motivated. • Pencils are not allowed. The exam consists of 4 sheets of paper. It must be returned with all the 4 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. FOR THE STUDENTS WHO DID THE COURSE PROJECT • Fill the box specifying the score achieved in the course project • Students who scored 12 points must solve either problem 1 or problem 2 with a time limit of 30 minutes • Students who scored 7 points must solve problem 3 and either problem 1 or problem 2 with a time limit of 50 minutes • Students who scored 5 points must solve problem 1 and problem 2 with a time limit of 50 minutes Scoring • A problem left unsolved will amount to zero points. • A completely wrong solution will amount to -3 points COURSE PROJECT SCORE FINAL TIME GRADES Problem 1 (7 points). Given the dataset below in which columns x0 and x1 identify the attributes while column class identifies the class attribute, (1) compute the average accuracy obtained by applying a tenfold crossvalidation using k-nearest neighbor with k equal to 3 and (2) discuss the computational complexity of classification using k-nearest neighbors with a plain table-based…
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