Machine Learning Regression: Linear Regression

Machine Learning Regression: Linear Regression

Professional Development

15 Qs

quiz-placeholder

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Machine Learning Regression: Linear Regression

Machine Learning Regression: Linear Regression

Assessment

Quiz

Computers

Professional Development

Medium

Created by

afizan azman

Used 32+ times

FREE Resource

15 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the goal of linear regression?

To analyze time series data

To predict categorical outcomes

To calculate the mean of the variables

To model the relationship between variables using a linear equation.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Explain the difference between simple linear regression and multiple linear regression.

Simple linear regression is more accurate than multiple linear regression.

In simple linear regression, there are two or more independent variables, whereas in multiple linear regression, there is only one independent variable.

In simple linear regression, there is only one independent variable, whereas in multiple linear regression, there are two or more independent variables.

Simple linear regression is used for categorical data, while multiple linear regression is used for continuous data.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the formula for a simple linear regression model?

y = ax + b

y = mx - b

y = cx + m

y = mx + c

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How is the best-fit line determined in linear regression?

By minimizing the sum of squared differences between observed values and predicted values using the method of least squares.

By flipping a coin

By choosing the highest value

By asking a magic eight ball

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the coefficient of determination (R-squared) in linear regression?

R-squared is a value between 0 and 100.

R-squared is a value between -1 and 1.

R-squared is a value between 0 and 1.

R-squared is a value between 0 and 2.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of the cost function in linear regression?

To calculate the accuracy of the model

To measure the performance of the model by calculating the difference between predicted and actual values.

To determine the number of features in the dataset

To select the learning rate for gradient descent

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are the assumptions of linear regression?

Linearity, Independence, Homoscedasticity, Skewness of residuals

Linearity, Dependence, Heteroscedasticity, Normality of residuals

Non-linearity, Independence, Homoscedasticity, Normality of residuals

Linearity, Independence, Homoscedasticity, Normality of residuals

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