Chapter 8. The Perceptron

In previous chapters we discussed generalized linear models that relate a linear combination of explanatory variables and model parameters to a response variable using a link function. In this chapter, we will discuss another linear model called the perceptron. The perceptron is a binary classifier that can learn from individual training instances, which can be useful for training from large datasets. More importantly, the perceptron and its limitations inspire the models that we will discuss in the final chapters.

Invented by Frank Rosenblatt at the Cornell Aeronautical Laboratory in the late 1950's, the development of the perceptron was originally motivated by efforts to simulate the human brain. A brain is composed ...

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