Data Mining MCQs With Answers

Computer MCQs 360May 3, 2024

0 11 1 minute read

Welcome to the Data Mining MCQs with Answers. In this post, we have shared Data Mining Online Test for different competitive exams. Find practice Data Mining Practice Questions with answers in Computer Tests exams here. Each question offers a chance to enhance your knowledge regarding Data Mining.

Data Mining Online Quiz

By presenting 3 options to choose from, Data Mining Quiz which cover a wide range of topics and levels of difficulty, making them adaptable to various learning objectives and preferences. You will have to read all the given answers of Data Mining Questions and Answers and click over the correct answer.

Test Name: Data Mining MCQ Quiz Practice
Type: Quiz Test
Total Questions: 40
Total Marks: 40
Time: 40 minutes

Note: Answer of the questions will change randomly each time you start the test. Practice each quiz test at least 3 times if you want to secure High Marks. Once you are finished, click the View Results button. If any answer looks wrong to you in Quizzes. simply click on question and comment below that question. so that we can update the answer in the quiz section.

Data Mining

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1 / 40

What is data mining?

Extracting patterns

Software testing

Database management

2 / 40

What is the purpose of feature selection in data mining?

Select relevant features

Cluster data points

Predict continuous values

3 / 40

________ is a process of discovering patterns in large datasets.

Data visualization

Data encryption

Data mining

4 / 40

________ is a technique used to segment customers based on behavior.

Regression analysis

Market basket analysis

Cluster analysis

5 / 40

________ is a technique used to visualize high-dimensional data.

Regression analysis

Dimensionality reduction

Clustering

6 / 40

________ is a model used to predict continuous values in data mining.

Regression

Classification

Clustering

7 / 40

________ is a technique used to handle imbalanced datasets in data mining.

Outlier detection

Data preprocessing

SMOTE

8 / 40

________ is a supervised learning technique that uses multiple models to classify data.

Dimensionality reduction

Ensemble learning

Clustering

9 / 40

________ is a method to assess the quality of discovered patterns in data mining.

Data cleaning

Model deployment

Evaluation

10 / 40

________ is a method to determine the optimal number of clusters in clustering algorithms.

Support vector machine

Elbow method

Apriori algorithm

11 / 40

What is the main challenge of clustering in data mining?

Feature selection

Determining the number of clusters

Handling outliers

12 / 40

What is the primary objective of association rule mining in data mining?

Classify data points

Predict future trends

Discover relationships

13 / 40

________ is a technique to group similar objects together in data mining.

Decision tree

Regression analysis

Clustering

14 / 40

________ is a technique used to handle noise and inconsistencies in data.

Feature selection

Data preprocessing

Regression analysis

15 / 40

________ is a measure of the accuracy of a classification model.

Accuracy

Support

Confidence

16 / 40

What is the purpose of frequent pattern mining in data mining?

Feature extraction

Discover recurring patterns

Handle missing values

17 / 40

What is the goal of anomaly detection in data mining?

Predict future trends

Discover associations

Identify unusual patterns

18 / 40

________ is a method to reduce the number of variables in data mining.

Dimensionality reduction

Data preprocessing

Feature extraction

19 / 40

________ is a technique used to classify data points into predefined classes.

Clustering

Supervised learning

Dimensionality reduction

20 / 40

________ is a technique used to predict categorical values in data mining.

Regression

Classification

Clustering

21 / 40

________ is a technique used to transform data into a more useful representation.

Dimensionality reduction

Data cleaning

Feature extraction

22 / 40

What is the goal of association rule mining?

Predict future trends

Classify data points

Discover relationships

23 / 40

________ is a method to assess the significance of discovered patterns in data mining.

Feature extraction

Data cleaning

Statistical testing

24 / 40

________ is a technique used to preprocess data for data mining.

Data cleaning

Software development

Network security

25 / 40

What is the role of cross-validation in data mining?

Software development

Data visualization

Evaluate model performance

26 / 40

What is the goal of pattern evaluation in data mining?

Handle missing values

Assess pattern quality

Cluster data points

27 / 40

________ is a technique used to quantify the strength of association between variables.

Regression analysis

Correlation

Decision tree

28 / 40

________ is a method to handle missing values in data mining.

Imputation

Data preprocessing

Outlier detection

29 / 40

________ is a supervised learning technique used in data mining.

Classification

Anomaly detection

Association rule mining

30 / 40

What is the purpose of sequence mining in data mining?

Natural language processing

Image processing

Discover patterns over time

31 / 40

________ is a technique used to visualize relationships between variables in data mining.

Outlier detection

Feature extraction

Scatter plot

32 / 40

What is the goal of regression analysis in data mining?

Cluster data points

Predict continuous values

Discover associations

33 / 40

What is the main goal of clustering in data mining?

Discover associations

Predict continuous values

Group similar data points

34 / 40

________ is a technique used to find frequent itemsets in transactional data.

Decision tree

K-means clustering

Apriori algorithm

35 / 40

What is the purpose of outlier detection in data mining?

Classify data points

Predict future trends

Identify unusual data points

36 / 40

________ is a measure of how often an itemset appears in a dataset.

Confidence

Support

Lift

37 / 40

What is the purpose of data cleaning in data mining?

Feature extraction

Prepare data for analysis

Predict future trends

38 / 40

________ is a technique used to analyze text data in data mining.

Natural language processing

Text mining

Image processing

39 / 40

________ is a method to identify outliers in data.

Dimensionality reduction

Outlier detection

Clustering analysis

40 / 40

________ is a technique used to find rules that predict the value of a dependent variable.

Association rule mining

Regression analysis

Decision tree

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Computer MCQs 360May 3, 2024

0 11 1 minute read