Linear Regression

Linear regression is a statistical method that is used to establish a relationship between a dependent variable and one or more independent variables. It is a linear approach to modeling the relationship between a dependent variable and one or more independent variables. The goal of linear regression is to find the best-fit line that describes the relationship between the variables. The best-fit line is the line that minimizes the sum of the squared differences between the observed values and the predicted values. Linear regression is widely used in data science and machine learning for predicting continuous values. It is used to model the relationship between a dependent variable and one or more independent variables, and to make predictions based on that relationship. Linear regression is a simple and powerful tool that can be used to analyze and model complex data sets.
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