Linear Regression in Machine Learning

Regression is the method used to predict the continuous variable in the target column or dependent variable based on independent features. It falls under the supervised technique. It is a statistical tool used to find out the relationship between the outcome variable, the dependent variable, and one or more variables often called independent variables. Linear regression is used for finding the linear relationship between the target and one or more predictors. Simple linear regression finds the relationship between the dependent (Y) and independent (X) and it tries to find the best fit line by minimizing the errors this fitness function says how good your model is, or you can define a cost function that measures how bad it is.