HomeMachine Learning MCQMachine Learning (ML) MCQ Questions with Answer 2022

Machine Learning (ML) MCQ Questions with Answer 2022

Machine Learning (ML) MCQ Questions with Answer 2022 – In Machine Learning Another important point to be noted is that every machine learning technique is classified as AI ones. However, not all AI could count as machine learning. Human knowledge is barely obtained by the experience throughout their life. For machines that knowledge is required to be fed by collecting enormous amounts of information on a specific application and fed thereto, machines also obtain in an exceedingly short period of your time. 

Table of Contents

1. Application of machine learning methods to large databases is called

A. data mining.

B. artificial intelligence

C. big data computing

D. internet of things

Answer: A. data mining.

2. If machine learning model output involves target variable then that model is called as

A. descriptive model

B. predictive model

C. reinforcement learning

D. all of the above

Answer: B. predictive model

<img width=

3. In what type of learning labelled training data is used

A. unsupervised learning

B. supervised learning

C. reinforcement learning

D. active learning

Answer: B. supervised learning

4. In following type of feature selection method we start with empty feature set

A. forward feature selection

B. backword feature selection

C. both a and b??

D. none of the above

Answer: A. forward feature selection

5. In PCA the number of input dimensiona are equal to principal components

A. true

B. false

Answer: A. true

6. PCA can be used for projecting and visualizing data in lower dimensions.

A. true

B. false

Answer: A. true

7. Which of the following is the best machine learning method?

A. scalable

B. accuracy

C. fast

D. all of the above

Answer: D. all of the above

8. What characterize unlabeled examples in machine learning

A. there is no prior knowledge

B. there is no confusing knowledge

C. there is prior knowledge

D. there is plenty of confusing knowledge

Answer: D. there is plenty of confusing knowledge

9. What does dimensionality reduction reduce?

A. stochastics

B. collinerity

C. performance

D. entropy

Answer: B. collinerity

10. Data used to build a data mining model.

A. training data

B. validation data

C. test data

D. hidden data

Answer: A. training data

Machine Learning MCQ Question with answer

11. The problem of finding hidden structure in unlabeled data is called…

A. supervised learning

B. unsupervised learning

C. reinforcement learning

D. none of the above

Answer: B. unsupervised learning

12. Of the Following Examples, Which would you address using an supervised learning Algorithm?

A. given email labeled as spam or not spam, learn a spam filter

B. given a set of news articles found on the web, group them into set of articles about the same story.

C. given a database of customer data, automatically discover market segments and group customers into different market segments.

D. find the patterns in market basket analysis

Answer: A. given email labeled as spam or not spam, learn a spam filter

13. Dimensionality Reduction Algorithms are one of the possible ways to reduce the computation time required to build a model

A. true

B. false

Answer: A. true

14. You are given reviews of few netflix series marked as positive, negative and neutral. Classifying reviews of a new netflix series is an example of

A. supervised learning

B. unsupervised learning

C. semisupervised learning

D. reinforcement learning

Answer: A. supervised learning

15. Which of the following is a good test dataset characteristic?

A. large enough to yield meaningful results

B. is representative of the dataset as a whole

C. both a and b

D. none of the above

Answer: C. both a and b

16. Following are the types of supervised learning

A. classification

B. regression

C. subgroup discovery

D. all of the above

Answer: D. all of the above

Trending Jobs In Machine Learning and Data Science

17. Type of matrix decomposition model is

A. descriptive model

B. predictive model

C. logical model

D. none of the above

Answer: A. descriptive model

18. Following is powerful distance metrics used by Geometric model

A. euclidean distance

B. manhattan distance

C. both a and b??

D. square distance

Answer: C. both a and b??

19. The output of training process in machine learning is

A. machine learning model

B. machine learning algorithm

C. null

D. accuracy

Answer: A. machine learning model

20. A feature F1 can take certain value: A, B, C, D, E, & F and represents grade of students from a college. Here feature type is

A. nominal

B. ordinal

C. categorical

D. boolean

Answer: B. ordinal

21. PCA is

A. forward feature selection

B. backword feature selection

C. feature extraction

D. all of the above

Answer: C. feature extraction

22. Dimensionality reduction algorithms are one of the possible ways to reduce the computation time required to build a model.

A. true

23. Which of the following techniques would perform better for reducing dimensions of a data set?

A. removing columns which have too many missing values

B. removing columns which have high variance in data

C. removing columns with dissimilar data trends

D. none of these

Answer: A. removing columns which have too many missing values

24. Supervised learning and unsupervised clustering both require which is correct according to the statement.

A. output attribute.

B. hidden attribute.

C. input attribute.

D. categorical attribute

Answer: C. input attribute.

25. What characterize is hyperplance in geometrical model of machine learning?

A. a plane with 1 dimensional fewer than number of input attributes

B. a plane with 2 dimensional fewer than number of input attributes

C. a plane with 1 dimensional more than number of input attributes

D. a plane with 2 dimensional more than number of input attributes

Answer: B. a plane with 2 dimensional fewer than number of input attributes

Machine Learning MCQ Question , machine learning Mcq question with answer

Additional Reading

READ MORE

If you found this post useful, don’t forget to share this with your friends, and if you have any query feel free to comment it in the comment section.

Thank you 🙂 Keep Learning !

Deepika
Deepikahttps://www.technicdude.in/
Hey, I'm Deepika a professional blogger and Experienced in Android Developer,Flutter Developer, PHP Web Developer. Technically sound Post graduate pursuing M.Tech in Computer Science and Engineering. I Love to gain every type of knowledge that's why i have done many courses in different fields like engineering and technology. Skilled in Java, HTML, CSS,Bootstrap,j query PHP, Python, SQL, C, C++,Firebase,MySQL,SQLite,JavaScript. Also I have learned Networking.
RELATED ARTICLES

LEAVE A REPLY

Please enter your comment!
Please enter your name here

- Advertisment -

Most Popular

- Advertisment -