Learn Machine Learning MCQ Questions with answers and solutions.

A

Admin • 832.27K Points
Coach

Q. The soft margin SVM is more preferred than the hard-margin SVM when-

(A) the data is linearly seperable
(B) The relationship is not symmetric between x and y in both.
(C) the data is not noisy and linearly seperable
(D) the data is noisy and linearly seperable

A

Admin • 832.27K Points
Coach

Q. Which of the following option is true regarding "Regression" and "Correlation"?
Note: y is dependent variable and x is independent variable.

(A) The relationship is symmetric between x and y in both.
(B) when irrelevant attributes have been removed from the data.
(C) The relationship is not symmetric between x and y in case of correlation but in case of regression it is symmetric.
(D) The relationship is symmetric between x and y in case of correlation but in case of regression it is not symmetric.

A

Admin • 832.27K Points
Coach

Q. A nearest neighbor approach is best used

(A) with large-sized datasets.
(B) 0.26
(C) when a generalized model of the data is desirable.
(D) when an explanation of what has been found is of primary importance.

A

Admin • 832.27K Points
Coach

Q. For the given weather data, what is the probability that players will play if weather is sunny

(A) 0.5
(B) density-based clustering
(C) 0.73
(D) 0.6

A

Admin • 832.27K Points
Coach

Q. Suppose we would like to perform clustering on spatial data such as the geometrical locations of houses. We wish to produce clusters of many different sizes and shapes. Which of the following methods is the most appropriate?

(A) decision trees
(B) to save space for storing the decision tree
(C) model-based clustering
(D) k-means clustering

A

Admin • 832.27K Points
Coach

Q. What would you do in PCA to get the same projection as SVD?

(A) transform data to zero mean
(B) transform data to zero median
(C) not possible
(D) none of these

A

Admin • 832.27K Points
Coach

Q. The . . . . . . . . of the hyperplane depends upon the number of features.

(A) dimension
(B) classification
(C) reduction
(D) none of the above

A

Admin • 832.27K Points
Coach

Q. What is the approach of basic algorithm for decision tree induction?

(A) greedy
(B) top down
(C) procedural
(D) step by step

A

Admin • 832.27K Points
Coach

Q. Can we extract knowledge without apply feature selection

(A) Yes
(B) 0.06
(C) ---
(D) ---

A

Admin • 832.27K Points
Coach

Q. Suppose there are 25 base classifiers. Each classifier has error rates of e = 0.35. Suppose you are using averaging as ensemble technique. What will be the probabilities that ensemble of above 25 classifiers will make a wrong prediction? Note: All classifiers are independent of each other

(A) 0.05
(B) validation data
(C) 0.07
(D) 0.09

Machine Learning MCQs with answers Page - 3

Q. The soft margin SVM is more preferred than the hard-margin SVM when-

Q. Which of the following option is true regarding "Regression" and "Correlation"?
Note: y is dependent variable and x is independent variable.

Q. A nearest neighbor approach is best used

Q. For the given weather data, what is the probability that players will play if weather is sunny

Q. Suppose we would like to perform clustering on spatial data such as the geometrical locations of houses. We wish to produce clusters of many different sizes and shapes. Which of the following methods is the most appropriate?

Q. What would you do in PCA to get the same projection as SVD?

Q. The . . . . . . . . of the hyperplane depends upon the number of features.

Q. What is the approach of basic algorithm for decision tree induction?

Q. Can we extract knowledge without apply feature selection

Q. Suppose there are 25 base classifiers. Each classifier has error rates of e = 0.35. Suppose you are using averaging as ensemble technique. What will be the probabilities that ensemble of above 25 classifiers will make a wrong prediction? Note: All classifiers are independent of each other

Add MCQ in this Category

Browse Categories

Machine Learning MCQs with answers Page - 3

Q. The soft margin SVM is more preferred than the hard-margin SVM when-

Q. Which of the following option is true regarding "Regression" and "Correlation"? Note: y is dependent variable and x is independent variable.

Q. A nearest neighbor approach is best used

Q. For the given weather data, what is the probability that players will play if weather is sunny

Q. Suppose we would like to perform clustering on spatial data such as the geometrical locations of houses. We wish to produce clusters of many different sizes and shapes. Which of the following methods is the most appropriate?

Q. What would you do in PCA to get the same projection as SVD?

Q. The . . . . . . . . of the hyperplane depends upon the number of features.

Q. What is the approach of basic algorithm for decision tree induction?

Q. Can we extract knowledge without apply feature selection

Q. Suppose there are 25 base classifiers. Each classifier has error rates of e = 0.35. Suppose you are using averaging as ensemble technique. What will be the probabilities that ensemble of above 25 classifiers will make a wrong prediction? Note: All classifiers are independent of each other

Add MCQ in this Category

Browse Categories

Q. Which of the following option is true regarding "Regression" and "Correlation"?
Note: y is dependent variable and x is independent variable.