SENATOROVAI/Normal-equation-solver-multiple-linear-regression-course
Multiple Linear Regression (MLR) models the linear relationship between a continuous dependent variable and two or more independent (explanatory) variables. Using the equation, it predicts outcomes based on multiple factors. Key assumptions include linearity, constant variance of residuals, and low correlation between independent variables.Solver
This project helps researchers and students understand how multiple factors influence a numerical outcome. It takes a dataset with various independent variables and a target dependent variable, then provides the mathematical formula to predict the outcome based on these inputs. This is useful for anyone studying the linear relationship between multiple explanatory factors and a single response.
Use this if you need a clear, explicit mathematical solution for how multiple independent variables linearly predict a continuous dependent variable in a research or educational context.
Not ideal if you need to solve complex regression problems where the number of independent variables exceeds the number of observations or where variables are highly correlated, as it assumes a uniquely defined solution.
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Jupyter Notebook
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MIT
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Last pushed
Mar 01, 2026
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