Quote:
Originally Posted by barbacot
When applying the onestep equation for linear regression, the vector of weights is obtained directly with all its components.
What if we impose from the beginning a restriction on the form of the hypothesis, say h(x)=3+w1*x1, instead of the full linear form h(x)=w0+w1*x1? In other words, we want w0 to be 3, no matter what.
Is the onestep equation still applicable somehow?
To compare, if we were to apply the gradient descent with the same constraint, we could do it very easy, just by keeping w0 fixed at its initial value (3).

You can transfer the fixed part to the other side of the equation, then solve for the remaining parameters only. In your example, it would be
solving for
only (the matrix
would be a column vector of
's).