Adaptive linear neurons and the convergence of learning
In this section, we will take a look at another type of single-layer neural network (NN): ADAptive LInear NEuron (Adaline). Adaline was published by Bernard Widrow and his doctoral student Tedd Hoff only a few years after Rosenblatt’s perceptron algorithm, and it can be considered an improvement on the latter (An Adaptive “Adaline” Neuron Using Chemical “Memistors”, Technical Report Number 1553-2 by B. Widrow and colleagues, Stanford Electron Labs, Stanford, CA, October 1960).
The Adaline algorithm is particularly interesting because it illustrates the key concepts of defining and minimizing continuous loss functions. This lays the groundwork for understanding other machine learning algorithms for classification, such as logistic regression, support vector machines, and multilayer neural networks, as well as linear regression models, which we will discuss in future chapters.
The key...
