Linear regression via least-squaresLinear regression is based on the idea of fitting a linear function through data points. In its basic form, the problem is as follows. we are given data In least-squares regression, the way we evaluate how well a candidate function ![]() Since a linear function ![]() We can formulate this as a least-squares problem: ![]() where ![]() The linear regression approach can be extended to multiple dimensions, that is, to problems where the output in the above problem contains more than one dimension (see here). It can also be extended to the problem of fitting non-linear curves. See also: |