https://en.wikipedia.org/wiki/ADALINE
Can Adaline(Adaptive Linear Neuron) be used to do a multiple linear regression being equivalent to the least squares method?
https://en.wikipedia.org/wiki/ADALINE
Can Adaline(Adaptive Linear Neuron) be used to do a multiple linear regression being equivalent to the least squares method?
Though conceptually they're very similar, your own reference points out their essential difference:
This update rule minimizes $E$, the square of the error, and is in fact the stochastic gradient descent update for linear regression.
Thus Adaline usually as a delta training rule for a (single) linear output layer in a ANN updates the model's weights incrementally based on individual training samples, which can lead to faster convergence of its error function and is suitable for online learning scenarios where data is continuously streaming. While the traditional OLS closed-form analytical approach for multiple linear regression in statistics requires all sample in a single batch.