Machine Learning Unit - 1 mcq

Machine Learning Unit - 1 mcq

 

1. What is Machine Learning (ML)?
(A) The autonomous acquisition of knowledge through the use of manual programs
(B) The selective acquisition of knowledge through the use of computer programs
(C) The selective acquisition of knowledge through the use of manual programs
(D) The autonomous acquisition of knowledge through the use of computer programs

Correct option is D

2. Father of Machine Learning (ML)
(A) Geoffrey Chaucer
(B) Geoffrey Hill
(C) Geoffrey Everest Hinton
(D) None of the above

Correct option is C

3. Which is FALSE regarding regression?
(A) It may be used for interpretation
(B) It is used for prediction
(C) It discovers causal relationships
(D) It relates inputs to outputs

Correct option is C

4. Choose the correct option regarding machine learning (ML) and artificial intelligence (AI)
(A) ML is a set of techniques that turns a dataset into a software
(B) AI is a software that can emulate the human mind
(C) ML is an alternate way of programming intelligent machines
(D) All of the above

Correct option is D

5. Which of the factors affect the performance of the learner system does not include?
(A) Good data structures
(B) Representation scheme used
(C) Training scenario
(D) Type of feedback

Correct option is A

6. In general, to have a well-defined learning problem, we must identity which of the following
(A) The class of tasks
(B) The measure of performance to be improved
(C) The source of experience
(D) All of the above

Correct option is D

7. Successful applications of ML
(A) Learning to recognize spoken words
(B) Learning to drive an autonomous vehicle
(C) Learning to classify new astronomical structures
(D) Learning to play world-class backgammon
(E) All of the above

Correct option is E

8. Which of the following does not include different learning methods
(A) Analogy
(B) Introduction
(C) Memorization
(D) Deduction

Correct option is B

9. In language understanding, the levels of knowledge that does not include?
(A) Empirical
(B) Logical
(C) Phonological
(D) Syntactic

Correct option is A

10. Designing a machine learning approach involves:-
(A) Choosing the type of training experience
(B) Choosing the target function to be learned
(C) Choosing a representation for the target function
(D) Choosing a function approximation algorithm
(E) All of the above

Correct option is E

11. Concept learning inferred a ______ valued function from training examples of its input and output.
(A) Decimal
(B) Hexadecimal
(C) Boolean
(D) All of the above

Correct option is C

12. Which of the following is not a supervised learning?
(A) Naive Bayesian
(B) PCA
(C) Linear Regression
(D) Decision Tree

Correct option is B

13. What is Machine Learning?
(i) Artificial Intelligence
(ii) Deep Learning
(iii) Data Statistics
(A) Only (i)
(B) (i) and (ii)
(C) All
(D) None

Correct option is B

14. What kind of learning algorithm for "Facial identities or facial expressions"?
(A) Prediction
(B) Recognition Patterns
(C) Generating Patterns
(D) Recognizing Anomalies

Correct option is B

15. Which of the following is not type of learning?
(A) Unsupervised Learning
(B) Supervised Learning
(C) Semi-unsupervised Learning
(D) Reinforcement Learning

Correct option is C

16. Real-Time decisions, Game AI, Learning Tasks, Skill Aquisition, and Robot Navigation are applications of which of the folowing
(A) Supervised Learning: Classification
(B) Reinforcement Learning
(C) Unsupervised Learning: Clustering
(D) Unsupervised Learning: Regression

Correct option is B

17. Targetted marketing, Recommended Systems, and Customer Segmentation are applications in which of the following
(A) Supervised Learning: Classification
(B) Unsupervised Learning: Clustering
(C) Unsupervised Learning: Regression
(D) Reinforcement Learning

Correct option is B

18. Fraud Detection, Image Classification, Diagnostic, and Customer Retention are applications in which of the following
(A) Unsupervised Learning: Regression
(B) Supervised Learning: Classification
(C) Unsupervised Learning: Clustering
(D) Reinforcement Learning

Correct option is B

19. Which of the following is not function of symbolic in the various function representation of Machine Learning?
(A) Rules in propotional Logic
(B) Hidden-Markov Models (HMM)
(C) Rules in first-order predicate logic
(D) Decision Trees

Correct option is B

20. Which of the following is not numerical functions in the various function representation of Machine Learning?
(A) Neural Network
(B) Support Vector Machines
(C) Case-based
(D) Linear Regression

Correct option is C

21. FIND-S Algorithm starts from the most specific hypothesis and generalize it by considering only ________ examples.
(A) Negative
(B) Positive
(C) Negative or Positive
(D) None of the above

Correct option is B

22. FIND-S algorithm ignores _______ examples.
(A) Negative
(B) Positive
(C) Both
(D) None of the above

Correct option is A

23. The Candidate-Elimination Algorithm represents the _____.
(A) Solution Space
(B) Version Space
(C) Elimination Space
(D) All of the above

Correct option is B

24. Inductive learning is based on the knowledge that if something happens a lot it is likely to be generally.
(A) True
(B) False

Correct option is A

25. Inductive learning takes examples and generalizes rather than starting with __________ knowledge.
(A) Inductive
(B) Existing
(C) Deductive
(D) None of these

Correct option is B

26. A drawback of the FIND-S is that, it assumes the consistency within the training set.
(A) True
(B) False

Correct option is A