Least Squares: Where Convenience Meets Optimality
Contents0.1. Computational Convenience2. Mean and Median3. OLS is BLUE4. LS is MLE with normal errorsConclusion 0. Least Squares is used almost everywhere when it comes to numerical optimization and regression tasks in machine learning. It aims at minimizing the Mean Squared Error (MSE) of a given model. Both L1 (sum of absolute values) and L2 (sum of squares) …
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