Top 350+ Solved Machine Learning (ML) MCQ Questions Answer

a. a and b

b. a and d

c. b, c and d

d. all of the above

a. o(mn)

b. o(tkn)

c. o(kn)

d. o(t2kn)

a. 100

b. 200

c. 4950

d. 5000

a. are better able to deal with missing and noisy data

b. typically assume an underlying distribution for the data

c. have trouble with large-sized datasets

d. are not able to explain their behavior

a. 0.0368

b. 0.0396

c. 0.0389

d. 0.0398

a. zero

b. three

c. singleton

d. two

a. 2k – 1 candidate association rules

b. 2k candidate association rules

c. 2k – 2 candidate association rules

d. 2k -2 candidate association rules

a. k-means clustering is a linear clustering algorithm.

b. k-means clustering aims to partition n observations into k clusters

c. k-nearest neighbor is same as k-means

d. k-means is sensitive to outlier

a. 1 and 2

b. 2 and 3

c. 2 and 4

d. 1, 2 and 4

a. flow-chart

b. structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label

c. flow-chart like structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label

d. none of the above

a. pessimistic pruning and optimistic pruning

b. postpruning and prepruning

c. cost complexity pruning and time complexity pruning

d. none of the options

a. 0.4

b. 0.6

c. 0.8

d. 0.42

a. it can be used for classification

b. ??it can be used for regression

c. ??it can be used in both classification and regression??

d. not useful in ml algorithm

a. measure performance over training data

b. measure performance over validation data

c. both of these

d. random selection of hyper parameters

a. 1 and 3

b. 1 and 2

c. 2 and 3

d. 1, 2 and 3