[D] Recursive Least Squares vs Gradient Descent for Neural Networks

I have been captivated by Recursive Least Squares (RLS) methods, particularly the approach that employs error prediction instead of matrix inversion. This method is quite intuitive. Let's consider a scenario where you need to estimate the true effect of four factors (color, gender, age, and weight) on blood sugar. To find the true impact of weight on blood sugar, it's necessary to eliminate the influence of every other factor on weight. This can be accomplished by using simple least squares …

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