![]() ![]() ![]() Mathematical equation for linear regression The prefix “extra” says that Extrapolation is where we find the values outside the data points using the best fit line.The prefix “inter” itself says that Interpolation is where we find the values (missing values) inside the data points using the best fit line.It is also called trend line or regression line and can be calculated by sum of squared errors, sum of absolute errors, root mean squared error.It is the line formed by the scatter plot for the given data points which gives the minimal residual error.In the linear regression, there can be many lines that can be drawn when graphed the given data points for the dependent variable vs independent variables, but we need to choose the best fit line which gives us the accurate value of the dependent variable with the minimum total predictor error is called as best fitted line. ![]() It can also be called as predictor variable, regressor, controlled variable, explanatory variable.These variables are basically used to assist in finding the value of dependent variable.In simple words, the variables other than dependent variables are called independent variables.Sometimes it is also called response variable, outcome variable.It is called dependent because its value changes based on the independent variables.It is the feature or the variable which should be predicted or can also be called as target variable.To define in the perspective of machine learning, we can say that linear regression is a supervised learning technique used to predict the value of the dependent variable/feature by forming the linear relationship with one or more independent variables/features with the help of best fitted straight line.When we combine the above two definitions, we can say that linear regression is the statistical method used to find the relationship between two or more variables by fixing the best fit line Straight line between the data points.Regression is statistical method used to analyze the relationship between two or more variables.Linear basically refers to the straight line or the relationship between two or more variables can be graphed as a straight line.Before understanding what linear regression model is, let’s try to understand few terms used in it and assumptions it has got. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |