1
Classification is a type of ______ learning technique.
Correct AnswerC. Supervised
☑ MCQ PRACTICE
Data Mining Unit 3
Practice objective questions for quick revision and examination preparation. Try answering each question before revealing the answer.
2
In the classification process, the model is built during the ______ phase.
Correct AnswerB. Learning
3
The main goal of a classifier is to predict ______ for new data.
Correct AnswerC. Class labels
4
A Decision Tree is a ______ structure.
Correct AnswerC. Tree-like
5
The topmost node in a decision tree is called the ______ node.
Correct AnswerB. Root
6
The attribute with the highest information gain is selected as the ______.
Correct AnswerB. Root node
7
The measure of impurity or uncertainty in data is called ______.
Correct AnswerB. Entropy
8
Information Gain is defined as the difference between original entropy and ______ entropy.
Correct AnswerA. Expected
9
ID3 algorithm was developed by ______.
Correct AnswerB. J. Ross Quinlan
10
The Bayesian classifier is based on ______ theorem.
Correct AnswerA. Bayes'
11
The Naïve Bayes classifier assumes ______ among predictors.
Correct AnswerB. Independence
12
In Bayes' theorem, ( P(H|X) ) represents the ______ probability.
Correct AnswerB. Posterior
13
Rule-based classification uses a set of ______ rules for classification.
Correct AnswerA. IF–THEN
14
Coverage of a rule measures the ______ of tuples covered by the rule.
Correct AnswerB. Percentage
15
Accuracy of a rule measures the percentage of tuples that are ______ classified.
Correct AnswerC. Correctly
16
Eager learners build a model ______ receiving new data tuples.
Correct AnswerA. Before
17
The most popular lazy learner is the ______ classifier.
Correct AnswerC. K-Nearest Neighbor
18
The commonly used value of K in K-NN algorithm is ______.
Correct AnswerD. 5
19
Euclidean distance measures the ______ between two points.
Correct AnswerA. Straight-line distance
20
The Manhattan distance is also called the ______ distance.
Correct AnswerB. Taxicab
Fill in the Blanks
21
Classification is used to categorize data into predefined ______.
AnswerClasses or labels
22
Decision trees can be used for both ______ and numerical data.
AnswerCategorical
23
Data classification is a two-step process, consisting of a __________________ and ___________________.
AnswerLearning and Classification
24
Entropy is a measure of ______ in the data.
AnswerImpurity or uncertainty
25
_____________________ is a statistical technique used to classify the data based on probabilistic reasoning.
AnswerBayesian Classification
26
Information gain is used to select the best attribute for ______.
AnswerSplitting or partitioning
27
The formula for Bayes’ theorem is _____________________.
AnswerP(H|X) = {P(X|H) × P(H)} / P(X)
28
The "IF" part of a rule is known as the ______.
AnswerAntecedent or precondition
29
The "THEN" part of a rule is known as the ______.
AnswerConsequent
30
Lazy learners perform generalization only when a ______ tuple is encountered.
AnswerTest
31
In K-NN, classification is done based on the majority class among the ______ neighbors.
AnswerK
32
_____________ distance measure is most commonly used in K-NN.
AnswerEuclidean