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Monthly Archives: December 2014

Notes on Perceptron. Part 5: Adaline

Adaptive linear neuron (or element) aka Adaline can be viewed as a variation of PLA with update scaled by the mismatch magnitude. While not the universally best choice for the classifier learning algorithm, Adaline can be viewed as an improvement over the original PLA.

Notes on Perceptron. Part 4: Convergence Theorem

This post discusses an outline of the the PLA convergence theorem. While the algorithm convergence is not obvious, its proof hinges only on two key inequalities.

Notes on Perceptron. Part 3: The Pocket Algorithm and Non-Separable Data

Here we look at the Pocket algorithm that addresses an important practical issue of PLA stability and the absence of convergence for non-separable training dataset.