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ML MCQ Question Bank

The document provides a 10 question machine learning (ML) multiple choice question (MCQ) bank with explanations for each answer. ML is defined as the autonomous acquisition of knowledge through computer programs (question 1). Key facts about ML are that it is a field of computer science, extracts patterns from raw data using algorithms, and allows systems to learn from experience without being programmed (question 2). ML algorithms improve their performance at tasks over time with experience (question 3). Common learning methods include memorization, analogy, and deduction but not introduction (question 4). Random forest is a widely used and effective ML algorithm based on bagging (question 5). High entropy in classification means partitions are not pure (question 6). ML methods include supervised

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1K views4 pages

ML MCQ Question Bank

The document provides a 10 question machine learning (ML) multiple choice question (MCQ) bank with explanations for each answer. ML is defined as the autonomous acquisition of knowledge through computer programs (question 1). Key facts about ML are that it is a field of computer science, extracts patterns from raw data using algorithms, and allows systems to learn from experience without being programmed (question 2). ML algorithms improve their performance at tasks over time with experience (question 3). Common learning methods include memorization, analogy, and deduction but not introduction (question 4). Random forest is a widely used and effective ML algorithm based on bagging (question 5). High entropy in classification means partitions are not pure (question 6). ML methods include supervised

Uploaded by

Tushar Gupta
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© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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ML MCQ Question bank 2 (RCS080)

01. What is Machine learning?

A. The autonomous acquisition of knowledge through the use of computer


programs
B. The autonomous acquisition of knowledge through the use of manual
programs
C. The selective acquisition of knowledge through the use of computer
programs
D. The selective acquisition of knowledge through the use of manual
programs
Answer : A
Explanation: “Machine learning” is the autonomous acquisition of knowledge
through the use of computer programs.

02. What is true about Machine Learning?

A. Machine Learning (ML) is the field of computer science


B. ML is a type of artificial intelligence that extract patterns out of raw
data by using an algorithm or method
C. The main focus of ML is to allow computer systems learn from
experience without being explicitly programmed or human intervention
D. All of the above
Answer : D
Explanation: All the statements are true about Machine Learning.

03. ML is a field of AI consisting of learning algorithms that?

A. Improve their performance


B. At executing some task
C. Over time with experience
D. All of the above
Answer : D
Explanation: Machine learning is a field of AI consisting of learning
algorithms that: Improve their performance (P), At executing some task (T),
Over time with experience (E).

04. Different learning methods do not include?

A. Memorization
B. Analogy
C. Introduction
D. Deduction
Answer : C
Explanation: Different learning methods in the ML do not include
Introdution.

05. Which of the following is a widely used and effective machine


learning algorithm based on the idea of bagging?

A. Decision Tree
B. Random Forest
C. Regression
D. Classification
Answer : B
Explanation: Random Forest

06. High entropy means that the partitions in classification are

A. pure
B. not pure
C. useful
D. useless
Answer : B
Explanation: Entropy is a measure of the randomness in the information
being processed So the higher the entropy, the harder it is to draw any
conclusions from that information. Entropy is a measure of disorder or purity
or unpredictability or uncertainty. So Low entropy means less uncertain and
high entropy means more uncertain.

07. Which of the following are ML methods?


A. Based on human supervision
B. Supervised Learning
C. Semi-reinforcement Learning
D. All of the above
Answer : A
Explanation: The following are various Machine learning methods based on
some broad categories: Based on human supervision, Unsupervised Learning,
Semi-supervised Learning, and Reinforcement Learning.

08. In language understanding, the levels of knowledge do not


include?

A. Phonological
B. Syntactic
C. Empirical
D. Logical
Answer : C
Explanation: In language understanding, the levels of knowledge do not
include empirical knowledge.

09. A machine learning problem involves four attributes plus a class. The
attributes have 3, 2, 2, and 2 possible values each. The class has 3 possible
values. How many maximum possible different examples are there?
A. 12
B. 24
C. 48
D. 72
Answer : D
Explanation: Maximum possible different examples are the products of the
possible values of each attribute and the number of classes so the result
would be
3 * 2 * 2 * 2 * 3 = 72

10. When performing regression or classification, which of the


following is the correct way to preprocess the data?

A. Normalize the data → PCA → training


B. PCA → normalize PCA output → training
C. Normalize the data → PCA → normalize PCA output → training
D. None of the above

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