Linear Regression (page 1 of 7)

The linear regression regressor machine learning algorithm is a simple and common type of supervised (known targets) machine learning algorithm. This algorithm attempts to model the relationship between one, two, or more features and a known (continuous) target by fitting a straight line to the training data. With the linear regression regressor, we still follow the same process of randomly splitting our data into training and testing data sets. With the sklearn LinearRegression algorithm, we do not have many hyper-parameters we can set to influence the training process (fit_intercept and normalize are probably the two most commonly used hyper-parameters).