Welcome to the Machine Learning MCQs Page

Dive deep into the fascinating world of Machine Learning with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Machine Learning, a crucial aspect of Data Science. In this section, you will encounter a diverse range of MCQs that cover various aspects of Machine Learning, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Data Science.

Check out the MCQs below to embark on an enriching journey through Machine Learning. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Data Science.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Machine Learning. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Machine Learning MCQs | Page 1 of 7

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Data Science Basics

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Data Analysis with Python

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05

Statistical Inference and Regression Models

06

Developing Data Products

Q1.

Which of the following can be used to generate balanced cross–validation groupings from a set of data?

createFolds

createSample

createResample

none of the mentioned

Discuss

Answer: (a).createFolds

Q2.

Point out the wrong statement.

Simple random sampling of time series is probably the best way to resample times series data.

Three parameters are used for time series splitting

Horizon parameter is the number of consecutive values in test set sample

All of the mentioned

Discuss

Answer: (a).Simple random sampling of time series is probably the best way to resample times series data.

Q3.

Which of the following function can be used to maximize the minimum dissimilarities?

sumDiss

minDiss

avgDiss

all of the mentioned

Discuss

Answer: (d).all of the mentioned

Q4.

Which of the following function can create the indices for time series type of splitting?

newTimeSlices

createTimeSlices

binTimeSlices

none of the mentioned

Discuss

Answer: (b).createTimeSlices

Q5.

Point out the correct statement.

Asymptotics are used for inference usually

Caret includes several functions to pre-process the predictor data

The function dummyVars can be used to generate a complete set of dummy variables from one or more factors

All of the mentioned

Discuss

Answer: (d).All of the mentioned

Q6.

Which of the following can be used to create sub–samples using a maximum dissimilarity approach?

minDissim

maxDissim

inmaxDissim

all of the mentioned

Discuss

Answer: (b).maxDissim

Q7.

caret does not use the proxy package.

True

False

May be True or False

Can't say

Discuss

Answer: (b).False

Q8.

Which of the following function can be used to create balanced splits of the data?

newDataPartition

createDataPartition

renameDataPartition

none of the mentioned

Discuss

Answer: (b).createDataPartition

Q9.

Which of the following package tools are present in caret?

pre-processing

feature selection

model tuning

all of the mentioned

Discuss

Answer: (d).all of the mentioned

Q10.

caret stands for classification and regression training.

True

False

May be True or False

Can't say

Discuss

Answer: (a).True

Page 1 of 7

Welcome to the Machine Learning MCQs Page

Machine Learning MCQs | Page 1 of 7

Explore more Topics under Data Science

Data Science Basics

Data Analysis with Python

Data Manipulation

Data Analysis and Research

Statistical Inference and Regression Models

Developing Data Products

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