This project focuses on building a linear regression model to predict a target variable based on multiple features in a dataset. The goal is to evaluate the model’s accuracy using key metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared (R²).
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This project focuses on building a linear regression model to predict a target variable based on multiple features in a dataset. The goal is to evaluate the model’s accuracy using key metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared (R²).
Zahid-coder-17/Linear-Regression-Model-Performance-Evaluation
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This project focuses on building a linear regression model to predict a target variable based on multiple features in a dataset. The goal is to evaluate the model’s accuracy using key metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared (R²).
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