☑ MCQ PRACTICE

Machine Learning Unit 1

Practice objective questions for quick revision and examination preparation. Try answering each question before revealing the answer.

📚 Machine Learning
📖 Unit 1
🎯 MCQs

Machine Learning — Unit 1

Introduction to Machine Learning, Concept Learning, Candidate Elimination, Perceptron and Linear Regression

1

Which of the following is not a type of machine learning?

ASupervised Learning
BReinforcement Learning
CUnsupervised Learning
DSequential Programming
Correct AnswerD
2

In supervised learning, the training data consists of:

AInput-output pairs
BOnly input features
COnly outputs
DRandom samples
Correct AnswerA
3

Which ML type is used for clustering problems?

ASupervised Learning
BReinforcement Learning
CUnsupervised Learning
DDeep Learning
Correct AnswerC
4

Reinforcement learning is based on:

AError correction
BRewards and punishments
CData clustering
DLinear regression
Correct AnswerD
5

In concept learning, the task is typically to infer:

AA data structure
BA target concept
CA clustering algorithm
DAn unsupervised pattern
Correct AnswerB
6

Candidate Elimination Algorithm maintains:

ATraining and test boundaries
BFeature and target boundaries
CSpecific and general hypotheses
DInput and output boundaries
Correct AnswerC
7

Version space contains:

AOnly general hypotheses
BAll hypotheses consistent with training data
COnly specific hypotheses
DInconsistent hypotheses
Correct AnswerB
8

Decision tree is mainly used for:

AClassification
BRegression
CClustering
DDimensionality reduction
Correct AnswerA
9

Linearly separable data can be classified using:

AK-means
BPerceptron
CNaive Bayes
DPCA
Correct AnswerB
10

Concept learning aims to:

AFind simplest hypothesis consistent with data
BMemorize data
CBuild complex model
DReduce memory
Correct AnswerA
11

A hypothesis refers to:

AMapping from input to output
BRandom guess
CNeural weight
DDataset
Correct AnswerA
12

Maximally specific hypothesis:

AAll generalizations
BIgnores negatives
CCovers only observed positives
DMost general
Correct AnswerC
13

Version space is:

AAll hypotheses
BConsistent hypotheses
CMinimum error hypotheses
DGeneral only
Correct AnswerB
14

Candidate Elimination maintains:

ASingle hypothesis
BMost general & most specific boundary
CRandom models
DRegression equations
Correct AnswerB
15

Recommendation systems mainly use:

ASupervised Learning
BUnsupervised Learning
CReinforcement Learning
DSemi-supervised Learning
Correct AnswerA
16

Legal move in checkers:

AForward
BBackward
CSide
DDiagonal
Correct AnswerD
17

______ is supervised learning task:

AReinforcement
BDimensionality reduction
CClustering
DClassification
Correct AnswerD
18

Most general hypothesis:

A((Sunny, Warm, Strong, Humid)
B((Sunny, ?, ?, ?)
C((?, ?, ?, ?)
D((φ, φ, φ, φ)
Correct AnswerC
19

Multiple linear regression predicts:

ALinear combination of inputs
BQuadratic
CProduct
DSquared sum
Correct AnswerA
20

In Find-S, '?' denotes:

ASpecific
BGeneral
CNull
DAlternative
Correct AnswerB
21

Perceptron purpose:

AClustering
BLinear classification
CDimensionality reduction
DProbability estimation
Correct AnswerB
22

When misclassification occurs perceptron:

AAdjusts weights
BStops
CResets
DIgnores
Correct AnswerA
23

Which is machine learning?

ASupervised
BManual
CMechanical
DStatic
Correct AnswerA
24

Supervised learning requires:

ANo output
BRandom data
CLabeled data
DUnlabeled
Correct AnswerC
25

Neuron input part:

AAxon
BDendrite
CSynapse
DNucleus
Correct AnswerB
26

Learning that improves with experience:

ATraditional
BMachine learning
CManual
DStatic
Correct AnswerB
27

Concept learning used for:

ARegression
BClassification
CClustering
DSorting
Correct AnswerB
28

Concept learning is:

AOptimization
BSearch problem
CGraph
DSorting
Correct AnswerB
29

Most general hypothesis symbol:

AØ
B?
CNULL
DMAX
Correct AnswerB
30

Version space contains:

AAll hypotheses
BConsistent hypotheses
CRandom
DNone
Correct AnswerB
31

Candidate Elimination proposed by:

AMcCarthy
BTom Mitchell
CRosenblatt
DHebb
Correct AnswerB
32

Perceptron uses:

ANon-linear
BStep function
CGaussian
DPolynomial
Correct AnswerB
33

Perceptron classifies:

ANon-linear
BRandom
CLinear
DClustered
Correct AnswerC
34

Linear separability means separation by:

ACurve
BCircle
CStraight line
DHyperbola
Correct AnswerC
35

Linear regression is used for:

AClassification
BPrediction
CClustering
DAssociation
Correct AnswerB
36

Linear regression minimizes:

AAbsolute error
BSquared error
CClassification error
DEntropy
Correct AnswerB
37

Perceptron output is:

AContinuous
BProbabilistic
CBinary
DMulticlass
Correct AnswerC

Fill in the Blanks

Machine Learning — Unit 1

38

Supervised learning uses ____________ data.

Answerlabeled
39

Most specific hypothesis = ____________

Answer(φ, φ, φ, φ)
40

Concept learning searches ____________ space.

Answerhypothesis
41

Find-S ignores ____________ examples.

Answernegative
42

Version space contains ____________ hypotheses.

Answerconsistent
43

Classification predicts ____________ values.

Answerdiscrete
44

Machine learning learns from ____________.

Answerexperience
45

Unsupervised learning uses ____________ data.

Answerunlabeled
46

Basic brain unit is ____________.

Answerneuron
47

Dendrites receive ____________ signals.

Answerinput
48

Axon transmits ____________ signals.

Answeroutput
49

Learning system includes ____________ element.

Answerlearning
50

Boolean function is learned in ____________.

Answerconcept learning.
51

Most general hypothesis is ____________

Answer?
52

Candidate Elimination maintains ____________ boundaries.

AnswerS and G
53

Perceptron is ____________ classifier.

Answerlinear
54

Linear regression predicts ____________ values.

Answercontinuous
55

Overfitting means model ____________ training data.

Answermemorizes
56

Good performance on unseen data is ____________.

Answergeneralization
57

ID3 uses ____________.

AnswerInformation Gain
58

Target concept is predicted in ____________.

Answerconcept learning
59

Hypothesis consistent with all data is ____________ hypothesis.

Answerconsistent
60

Straight line separates ____________ data.

Answerlinearly separable
61

Learning improves with ____________.

Answerexperience
62

Search problem formulation is used in ____________.

Answerconcept learning
63

Most specific symbol is ____________.

AnswerØ
64

Most general symbol is ____________.

Answer?
65

Regression predicts ____________ values.

Answercontinuous
66

Hypothesis space is searched in ____________.

Answerconcept learning
67

Candidate Elimination refines ____________.

Answerversion space
← Back to All MCQs