Machine LearningLesson 16Free preview

ML Regressions

This lesson is part of A.I. · All levels

Summary

Regression is used to predict continuous values such as price, temperature, or weight. Linear regression looks for the best straight line that approaches the entire data point by minimizing error. Regression results are usually measured by metrics such as Mean Squared Error (MSE).

Key points

Regression predicts a continuous numerical value, not a category.
Linear regression finds the y = mx + b line is best for the data.
The best line is selected by minimizing the error distance to the entire point.
General metrics for evaluating regression are MSE, RMSE, MAE, R-squared.

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