GitHub - mckinneymorgan/Linear-Polynomial-Regression: Machine learning linear regression that uses gradient descent to predict, train, and test on a given .csv file. The resulting best polynomial model is then graphed.

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Machine learning linear regression that uses gradient descent to predict, train, and test on a given .csv file. The resulting best polynomial model is then graphed.

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README for Linear and Polynomial Regression

Original author: Morgan McKinney 3/2021

Machine learning linear regression model that predicts, trains, and tests on a given .csv file. Algorithm uses stochastic gradient descent to perform linear or polynomial regression on datasets. Basis expansion is executed if indicated by user input. The resulting learned model is then visualised with a labelled graph. Furthermore, the final weights and mean squared error for every 10 epochs are outputted.

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Machine learning linear regression that uses gradient descent to predict, train, and test on a given .csv file. The resulting best polynomial model is then graphed.

gradient-descent datasets polynomial-regression

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