Machine Learning (ML) MCQ Questions with answers and solutions Page 62

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) We can not classify data correctly for given setting of hyper parameter C
(C) Can’t Say
(D) None of these

💬 Discuss

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

Published by Mr. Dubey ⭐ 109.99K Points at 14-Jun-2020 11:59 am in Machine Learning (ML)

Q. ______is the most drastic one and should be considered only when the dataset is quite large, the number of missing features is high, and any prediction could be risky.

(A) Removing the whole line
(B) Creating sub-model to predict those features
(C) Using an automatic strategy to input them according to the other known values
(D) All above

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✅ Correct Answer: (A) Removing the whole line

Published by Mr. Dubey ⭐ 109.99K Points at 14-Jun-2020 11:59 am in Machine Learning (ML)

Q. It's possible to specify if the scaling process must include both mean and standard deviation using the parameters________.

(A) with_mean=True/False
(B) with_std=True/False
(C) Both A & B
(D) None of the Mentioned

💬 Discuss

✅ Correct Answer: (C) Both A & B

Published by Mr. Dubey ⭐ 109.99K Points at 14-Jun-2020 11:59 am in Machine Learning (ML)

Q. Function used for linear regression in R is __________

(A) lm(formula, data)
(B) lr(formula, data)
(C) lrm(formula, data)
(D) regression.linear(formula, data)

💬 Discuss

✅ Correct Answer: (A) lm(formula, data)

Published by Mr. Dubey ⭐ 109.99K Points at 14-Jun-2020 11:59 am in Machine Learning (ML)

Q. In the mathematical Equation of Linear Regression Y = β1 + β2X + ϵ, (β1, β2) refers to __________

(A) (X-intercept, Slope)
(B) (Slope, X-Intercept)
(C) (Y-Intercept, Slope)
(D) (slope, Y-Intercept)

💬 Discuss

✅ Correct Answer: (C) (Y-Intercept, Slope)

Published by Mr. Dubey ⭐ 109.99K Points at 14-Jun-2020 11:59 am in Machine Learning (ML)

Q. ______can be adopted when it's necessary to categorize a large amount of data with a few complete examples or when there's the need to impose some constraints to a clustering algorithm.

(A) Supervised
(B) Semi-supervised
(C) Reinforcement
(D) Clusters

💬 Discuss

✅ Correct Answer: (B) Semi-supervised

Published by Admin ⭐ 38.37K Points at 20-Jun-2020 02:23 am in Machine Learning (ML)

Q. In the last decade, many researchers started training bigger and bigger models, built with several different layers that's why this approach is called_____.

(A) Deep learning
(B) Machine learning
(C) Reinforcement learning
(D) Unsupervised learning

💬 Discuss

✅ Correct Answer: (A) Deep learning

Published by Rakesh Kumar ⭐ 28.44K Points at 15-Jul-2020 08:39 am in Machine Learning (ML)

Q. there's a growing interest in pattern recognition and associative memories whose structure and functioning are similar to what happens in the neocortex. Such an approach also allows simpler algorithms called _____

(A) Regression
(B) Accuracy
(C) Modelfree
(D) Scalable

💬 Discuss

✅ Correct Answer: (C) Modelfree

Published by Ram Sharma ⭐ 193.88K Points at 02-Aug-2020 07:30 am in Machine Learning (ML)

Q. It's possible to specify if the scaling process must include both mean and standard deviation using the parameters________.

(A) with_mean=True/False
(B) with_std=True/False
(C) Both A & B
(D) None of the Mentioned

💬 Discuss

✅ Correct Answer: (C) Both A & B

Published by Vikash Gupta ⭐ 33.56K Points at 20-Jun-2020 08:15 am in Machine Learning (ML)

Q. Which of the following scale data by removing elements that don't belong to a given range or by considering a maximum absolute value.

(A) MinMaxScaler
(B) MaxAbsScaler
(C) Both A & B
(D) None of the Mentioned

💬 Discuss

✅ Correct Answer: (C) Both A & B

Published by Priyanka Tomar ⭐ 35.28K Points at 16-Jul-2020 12:25 am in Machine Learning (ML)

Machine Learning (ML) MCQs | Page - 62

Q. ______is the most drastic one and should be considered only when the dataset is quite large, the number of missing features is high, and any prediction could be risky.

Q. It's possible to specify if the scaling process must include both mean and standard deviation using the parameters________.

Q. Function used for linear regression in R is __________

Q. In the mathematical Equation of Linear Regression Y = β1 + β2X + ϵ, (β1, β2) refers to __________

Q. ______can be adopted when it's necessary to categorize a large amount of data with a few complete examples or when there's the need to impose some constraints to a clustering algorithm.

Q. In the last decade, many researchers started training bigger and bigger models, built with several different layers that's why this approach is called_____.

Q. there's a growing interest in pattern recognition and associative memories whose structure and functioning are similar to what happens in the neocortex. Such an approach also allows simpler algorithms called _____

Q. It's possible to specify if the scaling process must include both mean and standard deviation using the parameters________.

Q. Which of the following scale data by removing elements that don't belong to a given range or by considering a maximum absolute value.

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