Least Square Method(Least Mean Square) The way how to obtain parameters to minimize the sum of data and residual(error). In other words, to obtain parameters(a, b) with minimum E. - y = f(x) : Linear - ei : Residual(Error) - (xi, yi) : Data - a, b : Parameters y = f(x) : Linear Regression It can be expressed as below. Error Distance between the point and y. Sum of the square errors Matrix Equati..
