Microsoft DP-100 Designing and Implementing a Data Science Solution on Azure 09 31Oct2024 - Practice Quiz

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Question 1 of 30

A data scientist is tasked with predicting housing prices based on various features such as square footage, number of bedrooms, and location. After applying a linear regression model, the data scientist notices that the model\'s R-squared value is 0.85. However, upon further analysis, they find that the residuals are not randomly distributed and show a pattern. What should the data scientist consider doing next to improve the model\'s performance?

Investigate potential non-linear relationships and consider using polynomial regression or transforming features.

Increase the number of features in the model without assessing their relevance.

Rely solely on the R-squared value to determine the model's effectiveness.

Remove all outliers from the dataset without further analysis.

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