Convex Optimization in R

Last Updated on August 22, 2019

Optimization is a big part of machine learning. It is the core of most popular methods, from least squares regression to artificial neural networks.

In this post you will discover recipes for 5 optimization algorithms in R.

These methods might be useful in the core of your own implementation of a machine learning algorithm. You may want to implement your own algorithm tuning scheme to optimize the parameters of a model for some cost function.

A good example may be the case where you want to optimize the hyper-parameters of a blend of predictions from an ensemble of multiple child models.

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Golden Section Search

Golden Section Search is a Line Search method for Global Optimization in one-dimension. It is a Direct Search (Pattern Search) method as it samples the function to approximate a derivative rather than computing it directly.

The Golden Section Search is related to pattern searches of discrete ordered lists such as the Binary Search and the Fibonacci Search. It is related
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