Computer Engineering - Machine Learning

Full exam

DIPARTIMENTO DI ELETTRONICA, INFORMAZIONE E BIOINGEGNERIA Politecnico di Milano Machine Learning (Code: 097683)June 28, 2022 Surname: Name: Student ID: Row: Column:Time:2hoursMaximumMarks:33 ˆThe following exam is composed of8 exercises(one per page). The rst page needs to be lled with yourname, surname and student ID. The following pages should be used only in the large squarespresent on each page. Any solution provided either outside these spaces orwithout a motivationwill not be considered for the nal mark. ˆDuring this exam you arenot allowed to use electronic devices, such as laptops, smartphones, tablets and/or similar. As well, you are not allowed to bring with you any kind of note, book, written scheme, and/or similar. You are also not allowed to communicate with other students during the exam. ˆThe rst reported violation of the above-mentioned rules will be annotated on the exam and will be considered for the nal mark decision. The second reported violation of the above-mentioned rules will imply the immediate expulsion of the student from the exam room and theannulment of the exam. ˆYou are allowed to write the exam either with a pen (black or blue) or a pencil. It is your responsibility to provide a readable solution. We will not be held accountable for accidental partial or total cancellation of the exam. ˆThe exam can be written either inEnglishorItalian. ˆYou are allowed to withdraw from the exam at any time without any penalty. You are allowed to leave the room not early than half the time of the duration of the exam. You are not allowed to keep the text of the exam with you while leaving the room. ˆThree of the points will be given on the basis on how quick you are in solving the exam.If you nish earlier than 45 min before the end of the exam you will get 3 points, if you nish earlier than 30 min you will get 2 points and if you nish earlier than 15 min you will get 1 point (the points cannot be accumulated). ˆThe box on Page 10 can only be used to complete the Exercises 7, and/or 8.Ex. 1Ex. 2Ex. 3Ex. 4Ex. 5Ex. 6Ex. 7Ex. 8TimeTot. / 7/ 7/ 2/ 2/ 2/ 2/ 4/ 4/ 3/ 33 Student's name: Please go on to the next page. . . Computer Science Computer Science | Machine Learning Page 2 of 10 Exercise 1 (7marks) Describe the Bayesian Linear Regression method and how it compares to Ridge Regression.Student's name: Please go on to the next page. . . Computer Science Computer Science | Machine Learning Page 3 of 10 Exercise 2 (7marks) Explain what the Kernel Trick is, what it is used for, and in which ML methods it can be used.Student's name: Please go on to the next page. . . Computer Science Computer Science | Machine Learning Page 4 of 10 Exercise 3 (2marks) Assume you have been given a dataset with input matrixXand target vectory. Consider the following snippet of code: 1 p c a = PCA ( ) 2 p c a . f i t ( X , y ) 3 e x p l a i n e d = p c a . e x p l a i n e dv a r i a n c e 4 T = p c a . t r a n s f o r m (X) 5 e x p l a i n e dv a r i a n c e = np . cumsum ( e x p l a i n e d ) / sum( e x p l a i n e d ) 6 Tt i l d e = T [ : , e x p l a i n e dv a r i a n c e