Docsity
Docsity
Prepare for your exams
Prepare for your exams

Study with the several resources on Docsity

Earn points to download
Earn points to download

Earn points by helping other students or get them with a premium plan

Guidelines and tips
Guidelines and tips
Sell on Docsity
Sell on Docsity
Docsity AI
Docsity AI
Log inSign up

Prepare for your exams

Study with the several resources on Docsity

Find documents

Prepare for your exams with the study notes shared by other students like you on Docsity

Search for your university

Find the specific documents for your university's exams

Docsity AINEW

Summarize your documents, ask them questions, convert them into quizzes and concept maps

Explore questions

Clear up your doubts by reading the answers to questions asked by your fellow students

Earn points to download

Earn points by helping other students or get them with a premium plan

Share documents
download point icon20 Points

For each uploaded document

Answer questions
download point icon5 Points

For each given answer (max 1 per day)

All the ways to get free points
Get points immediately

Choose a premium plan with all the points you need

Study Opportunities

Choose your next study program

Get in touch with the best universities in the world. Search through thousands of universities and official partners

Community

Ask the community

Ask the community for help and clear up your study doubts

Free resources

Our save-the-student-ebooks!

Download our free guides on studying techniques, anxiety management strategies, and thesis advice from Docsity tutors

Machine Learning & Data Mining Multiple Choice Practice ..., Study notes of Machine Learning

University of Kufa (UK)Machine Learning

Section A. Answer all questions. 1. What are the three essential components of a learning system? Give a definition of each. Give an example of each ...

Typology: Study notes

2021/2022

Uploaded on 09/07/2022

adnan_95
adnan_95 🇮🇶

4.3

(39)

918 documents

1 / 4

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
COMP61011
Two hours
QUESTION PAPER MUST NOT BE REMOVED FROM EXAM ROOM
UNIVERSITY OF MANCHESTER
SCHOOL OF COMPUTER SCIENCE
Machine Learning & Data Mining
Multiple Choice Practice Questions
Examination date not specified
Time: Examination time not specified
The use of electronic calculators is permitted provided they are not programmable and
do not store text.
Page 1 of 4 [PTO]
pf3
pf4

Partial preview of the text

Download Machine Learning & Data Mining Multiple Choice Practice ... and more Study notes Machine Learning in PDF only on Docsity!

Two hours

QUESTION PAPER MUST NOT BE REMOVED FROM EXAM ROOM

UNIVERSITY OF MANCHESTER

SCHOOL OF COMPUTER SCIENCE

Machine Learning & Data Mining

Multiple Choice Practice Questions

Examination date not specified Time: Examination time not specified

The use of electronic calculators is permitted provided they are not programmable and do not store text.

Page 1 of 4 [PTO]

Section A

Answer all questions.

  1. What are the three essential components of a learning system? Give a definition of each. Give an example of each, including equations where necessary. (1 mark) A. Model, gradient descent, learning algorithm B. Error function, model, learning algorithm C. Accuracy, Sensitivity, Specificity D. Model, error function, cost function
  2. The error function most suited for gradient descent using logistic regression is

A. The entropy function B. The squared error C. The cross-entropy function D. The number of mistakes

  1. After SVM learning, each Lagrange multiplier αi takes either zero or non-zero value. What does it indicate in each situation? A. A non-zero αi indicates the datapoint i is a support vector, meaning it touches the margin boundary. B. A non-zero αi indicates that the learning has not yet converged to a global mini- mum. C. A zero αi indicates that the datapoint i has become a support vector datapoint, on the margin. D. A zero αi indicates that the learning process has identified support for vector i.

Page 2 of 4

  1. Boosting is said to be a good classifier because A. It creates all ensemble members in parallel, so their diversity can be boosted. B. It attempts to minimise the margin distribution. C. It attempts to maximise the margins on the training data D. None of the above
  2. What does it mean to perform a data bootstrap? A. To sample M features with replacement from the total M. B. To sample M features without replacement from the total M. C. To sample N examples with replacement from the total N. D. To sample N examples without replacement from the total N.
  3. A doctor can run a test for the horrible disease Examophobia. The test has two possible outcomes: positive and negative. It is known that among all students, if Examophobia is present, the test comes out positive 80% of the time, and negative 20% of the time. If Examophobia is not present, the test comes out positive 1% of the time, negative 99%. Among the general student population, Examophobia is known to occur in 35% of all students. A student enters the clinic and tests positive for the disease. What is the probability they really have Examophobia? A. 0. B. 0. C. 0. D. 0.

Page 4 of 4 END OF EXAMINATION