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Machine Learning MCQ Questions: Practice and Test Your Knowledge

Ace your exams, tests, interviews, and quizzes with our comprehensive set of Machine Learning Multiple Choice Questions (MCQs). Covering essential topics in Machine Learning, enhance your understanding and boost your performance. Start practicing now Page-6 section-1

Each section contains 100 MCQs on Machine Learning .
51
Can we calculate the skewness of variables based on mean and median?
Discuss
Answer & Solution
Answer: Option B
No explanation is given for this question. Let's Discuss on Board
52
It is possible to design a Linear regression algorithm using a neural network?
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Answer & Solution
Answer: Option A
No explanation is given for this question. Let's Discuss on Board
53
If Linear regression model perfectly first i.e., train error is zero, then . . . . . . . .
Discuss
Answer & Solution
Answer: Option C
No explanation is given for this question. Let's Discuss on Board
54
Increase in size of a convolutional kernel would necessarily increase the performance of a convolutional network.
Discuss
Answer & Solution
Answer: Option B
No explanation is given for this question. Let's Discuss on Board
55
To control the size of the tree, we need to control the number of regions. One approach to do this would be to split tree nodes only if the resultant decrease in the sum of squares error exceeds some threshold. For the described method, which among the following are true?
a. It would, in general, help restrict the size of the trees
b. It has the potential to affect the performance of the resultant regression/classification model
c. It is computationally infeasible
Discuss
Answer & Solution
Answer: Option A
No explanation is given for this question. Let's Discuss on Board
56
Which of the following is the difference between stacking and blending?
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Answer & Solution
Answer: Option D
No explanation is given for this question. Let's Discuss on Board
57
Logistic regression is a . . . . . . . . regression technique that is used to model data having a . . . . . . . . outcome.
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Answer & Solution
Answer: Option D
No explanation is given for this question. Let's Discuss on Board
58
You are given reviews of few netflix series marked as positive, negative and neutral. Classifying reviews of a new netflix series is an example of
Discuss
Answer & Solution
Answer: Option A
Solution:
In supervised learning, the model is trained on a labeled dataset, where each input (in this case, the Netflix reviews) is associated with a corresponding output label (positive, negative, or neutral).
The goal is to teach the model to predict the correct label for new, unseen data based on the patterns it learned from the labeled examples.

Supervised learning uses labeled data to train the model, and the model is evaluated based on how accurately it classifies new, unlabeled data.
In this case, since the reviews are already labeled as positive, negative, or neutral, this is a typical example of supervised learning.
59
In following type of feature selection method we start with empty feature set
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Answer & Solution
Answer: Option A
No explanation is given for this question. Let's Discuss on Board
60
Neural Networks are complex . . . . . . . . with many parameters.
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Answer & Solution
Answer: Option A
No explanation is given for this question. Let's Discuss on Board