Impact-Site-Verification: dbe48ff9-4514-40fe-8cc0-70131430799e

Search This Blog

MATLAB Simulation of Perceptron Learning

In machine learning, the perceptron is an algorithm for supervised learning of binary classifiers (functions that can decide whether an input, represented by a vector of numbers, belongs to some specific class or not). It is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector.

In short the hidden layer provides non-linearity. You can think of each hidden neuron as a single logistic regression. Each logistic regression has a linear decision boundary. With more than one linear, non-parallel lines, you can draw a convex boundary - more lines, more flexibility. The combined boundary is the final output layer. 


1 comment:

Popular Posts