/linear/regression

Get the linear regression result for the dataset. This will return the result in the form of y = mx + c because linear regression is actually a straight line curve. x_samples and y_samples are a set of sample values in this curve so we can plot it offline using a graph tool such as MS Excel. In the result we have the coefficent and y_interceptor values which represents the m and c of the y = mx + c. So with these values we can predict any y value for a given value in x dimension.

For example, imagine we have a data set with x axis representing the GDP of country and y axis has the happiness score. Using the coefficent and y_interceptor (m and c in y = mx + c), we can predict how happy is a country quantitatively by supplying the GDP value to x.