In linear regression model, how can we define cost function. also after defining cost function how to minimize the error term?
Statistical programs, such as R, typicall use Least Squares estimation. It's a deterministic algorithm that makes a linear model find its optimal tuple of parameters. Because of this, you don't have to worry about the choice of a loss function.
In case you wanted to train your linear regression with a gradient descent algorithm, instead, you'd have to specify a loss function to run it. Classical loss functions for regression are: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE).