Linear Regression

Linear regression finds the best straight line that describes the relationship between the free variable X and the bound variable y. This model minimizes the difference between the predicted value and the actual value, and then produces the slope coefficient and the cut-off point. After being trained, the model can estimate the value of y for the value of x that has never been seen before. In scikit-learn, the entire process is enough with fit() on the training data and then predict() on the test data.