Machine Learning MCQ Questions with answers and solutions Page 13

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

(A) TRUE
(B) Statistics and Informal Retrieval
(C) ---
(D) ---

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✅ Correct Answer: (A) TRUE

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. What are the two methods used for the calibration in Supervised Learning?

(A) Platt Calibration and Isotonic Regression
(B) variable f1 is an example of ordinal variable
(C) Both A and B
(D) None of these

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✅ Correct Answer: (A) Platt Calibration and Isotonic Regression

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. A student Grade is a variable F1 which takes a value from A,B,C and D. Which of the following is True in the following case?

(A) variable f1 is an example of nominal variable
(B) nonlinear
(C) it doesnt belong to any of the mentioned categories
(D) it belongs to both ordinal and nominal category

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✅ Correct Answer: (B) nonlinear

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. Regression trees are often used to model . . . . . . . . data.

(A) linear
(B) proababilistic model
(C) categorical
(D) symmetrical

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✅ Correct Answer: (B) proababilistic model

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. Support Vector Machine is

(A) logical model
(B) We can not classify data correctly for given setting of hyper parameter C
(C) geometric model
(D) none of the above

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✅ Correct Answer: (C) geometric model

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. Suppose you are building a SVM model on data X. The data X can be error prone which means that you should not trust any specific data point too much. Now think that you want to build a SVM model which has quadratic kernel function of polynomial degree 2 that uses Slack variable C as one of it's hyper parameter.What would happen when you use very large value of C(C->infinity)?

(A) We can still classify data correctly for given setting of hyper parameter C
(B) 2 and 3
(C) Can't Say
(D) None of these

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✅ Correct Answer: (A) We can still classify data correctly for given setting of hyper parameter C

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. Supervised learning and unsupervised clustering both require at least one

(A) hidden attribute.
(B) output attribute.
(C) input attribute.
(D) categorical attribute.

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✅ Correct Answer: (A) hidden attribute.

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. Which of the following sentences are correct in reference to Information gain? a. It is biased towards single-valued attributes b. It is biased towards multi-valued attributes c. ID3 makes use of information gain d. The approact used by ID3 is greedy

(A) a and b
(B) a and d
(C) b, c and d
(D) all of the above

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✅ Correct Answer: (C) b, c and d

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. Even if there are no actual supervisors . . . . . . . . learning is also based on feedback provided by the environment

(A) Supervised
(B) Reinforcement
(C) Unsupervised
(D) None of the above

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✅ Correct Answer: (B) Reinforcement

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. A feature F1 can take certain value: A, B, C, D, E & F and represents grade of students from a college. Which of the following statement is true in following case?

(A) Feature F1 is an example of nominal variable.
(B) Feature F1 is an example of ordinal variable.
(C) It doesn't belong to any of the above category.
(D) Both of these

💬 Discuss

✅ Correct Answer: (B) Feature F1 is an example of ordinal variable.

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Machine Learning MCQs with answers Page - 13

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

Q. What are the two methods used for the calibration in Supervised Learning?

Q. A student Grade is a variable F1 which takes a value from A,B,C and D. Which of the following is True in the following case?

Q. Regression trees are often used to model . . . . . . . . data.

Q. Support Vector Machine is

Q. Supervised learning and unsupervised clustering both require at least one

Q. Which of the following sentences are correct in reference to Information gain? a. It is biased towards single-valued attributes b. It is biased towards multi-valued attributes c. ID3 makes use of information gain d. The approact used by ID3 is greedy

Q. Even if there are no actual supervisors . . . . . . . . learning is also based on feedback provided by the environment

Q. A feature F1 can take certain value: A, B, C, D, E & F and represents grade of students from a college. Which of the following statement is true in following case?

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