Machine Learning MCQ Questions with answers and solutions Page 19

Q. If two variables are correlated, is it necessary that they have a linear relationship?

(A) Yes
(B) It is more likely for X1 to be included in the model
(C) ---
(D) ---

💬 Discuss

✅ Correct Answer: (B) It is more likely for X1 to be included in the model

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:22 pm in Machine Learning

Q. Suppose we fit "Lasso Regression" to a data set, which has 100 features (X1,X2...X100). Now, we rescale one of these feature by multiplying with 10 (say that feature is X1), and then refit Lasso regression with the same regularization parameter. Now, which of the following option will be correct?

(A) It is more likely for X1 to be excluded from the model
(B) Decision Tree
(C) Can't say
(D) None of these

💬 Discuss

✅ Correct Answer: (B) Decision Tree

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:22 pm in Machine Learning

Q. Which of the following is not supervised learning?

(A) PCA
(B) reinforcement learning
(C) Naive Bayesian
(D) Linerar regression

💬 Discuss

✅ Correct Answer: (A) PCA

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:22 pm in Machine Learning

Q. Some telecommunication company wants to segment their customers into distinct groups ,this is an example of

(A) supervised learning
(B) random_state
(C) unsupervised learning
(D) data extraction

💬 Discuss

✅ Correct Answer: (C) unsupervised learning

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:22 pm in Machine Learning

Q. . . . . . . . . which can accept a NumPy RandomState generator or an integer seed.

(A) make_blobs
(B) is commonly used for dimensionality reduction
(C) test_size
(D) training_size

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✅ Correct Answer: (B) is commonly used for dimensionality reduction

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:22 pm in Machine Learning

Q. The kernel trick

(A) can be applied to every classification algorithm
(B) a and d
(C) changes ridge regression so we solve a d × d linear system instead of an n × n system, given n sample points with d features
(D) exploits the fact that in many learning algorithms, the weights can be written as a linear combination of input points

💬 Discuss

✅ Correct Answer: (D) exploits the fact that in many learning algorithms, the weights can be written as a linear combination of input points

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:22 pm in Machine Learning

Q. Suppose on performing reduced error pruning, we collapsed a node and observed an improvement in the prediction accuracy on the validation set. Which among the following statements are possible in light of the performance improvement observed? (a) The collapsed node helped overcome the effect of one or more noise affected data points in the training set (b) The validation set had one or more noise affected data points in the region corresponding to the collapsed node (c) The validation set did not have any data points along at least one of the collapsed branches (d) The validation set did have data points adversely affected by the collapsed node

(A) a and b
(B) decreases with the increase in size of the data
(C) b, c and d
(D) all of the above

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✅ Correct Answer: (D) all of the above

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:22 pm in Machine Learning

Q. The number of iterations in apriori . . . . . . . . Select one:

(A) increases with the size of the data
(B) positive
(C) increases with the size of the maximum frequent set
(D) decreases with increase in size of the maximum frequent set

💬 Discuss

✅ Correct Answer: (C) increases with the size of the maximum frequent set

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:22 pm in Machine Learning

Q. PCA is

(A) forward feature selection
(B) backword feature selection
(C) feature extraction
(D) all of the above

💬 Discuss

✅ Correct Answer: (C) feature extraction

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:22 pm in Machine Learning

Q. Which statement is true about prediction problems?

(A) the output attribute must be categorical.
(B) the output attribute must be numeric.
(C) the resultant model is designed to determine future outcomes.
(D) the resultant model is designed to classify current behavior.

💬 Discuss

✅ Correct Answer: (D) the resultant model is designed to classify current behavior.

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:22 pm in Machine Learning

Machine Learning MCQs with answers Page - 19

Q. If two variables are correlated, is it necessary that they have a linear relationship?

Q. Suppose we fit "Lasso Regression" to a data set, which has 100 features (X1,X2...X100). Now, we rescale one of these feature by multiplying with 10 (say that feature is X1), and then refit Lasso regression with the same regularization parameter. Now, which of the following option will be correct?

Q. Which of the following is not supervised learning?

Q. Some telecommunication company wants to segment their customers into distinct groups ,this is an example of

Q. . . . . . . . . which can accept a NumPy RandomState generator or an integer seed.

Q. The kernel trick

Q. The number of iterations in apriori . . . . . . . . Select one:

Q. PCA is

Q. Which statement is true about prediction problems?

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