Why a classical Perceptron (i.e., a single layer of linear threshold units) is not preferable to use?

A classical Perceptron, which is a single layer of linear threshold units, is not preferable to use because it has several limitations that make it less effective than other neural network models. Here are some of the main reasons: Limited Representational Power: A Perceptron can only learn linear decision boundaries, which makes it less effective for more complex problems that require non-linea..

2023.03.04