Machine Learning, Linear Regression, Algorithms, Data Science, Data Visualization.
better fit. Key Assumptions Linearity: The relationship between the independent and dependent variables should be linear. Independence: The residuals should be independent. Homoscedasticity: The residuals should have constant variance. Limitations Oversimplification: May not capture complex