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Question 171 - MLS-C01 discussion

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A Machine Learning Specialist is attempting to build a linear regression model.

Given the displayed residual plot only, what is the MOST likely problem with the model?

A.
Linear regression is inappropriate. The residuals do not have constant variance.
Answers
A.
Linear regression is inappropriate. The residuals do not have constant variance.
B.
Linear regression is inappropriate. The underlying data has outliers.
Answers
B.
Linear regression is inappropriate. The underlying data has outliers.
C.
Linear regression is appropriate. The residuals have a zero mean.
Answers
C.
Linear regression is appropriate. The residuals have a zero mean.
D.
Linear regression is appropriate. The residuals have constant variance.
Answers
D.
Linear regression is appropriate. The residuals have constant variance.
Suggested answer: A

Explanation:

A residual plot is a type of plot that displays the values of a predictor variable in a regression model along the x-axis and the values of the residuals along the y-axis. This plot is used to assess whether or not the residuals in a regression model are normally distributed and whether or not they exhibit heteroscedasticity. Heteroscedasticity means that the variance of the residuals is not constant across different values of the predictor variable. This violates one of the assumptions of linear regression and can lead to biased estimates and unreliable predictions. The displayed residual plot shows a clear pattern of heteroscedasticity, as the residuals spread out as the fitted values increase. This indicates that linear regression is inappropriate for this data and a different model should be used.References:

Regression - Amazon Machine Learning

How to Create a Residual Plot by Hand

How to Create a Residual Plot in Python

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asked 16/09/2024
Oscar Luis Garza Ruiz
40 questions
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