See also slides for curve fitting, regression, colab link
Transclude of thoughts/university/twenty-four-twenty-five/sfwr-4ml3/ols_and_kls.py
curve fitting.
how do we fit a distribution of data over a curve?
Given a set of data points
- (or )
ols.
Ordinary Least Squares (OLS)
Let be the prediction of a model , is the error, minimize
In the case of 1-D ordinary least square, the problems equates find to minimize
Optimal solution
where , , ,
Hyperplane equation
where is the intercept (bias)
Homogenous hyperplane:
minimize
Thus we can find