Tutorial by Examples

At its core a perceptron model is one of the simplest supervised learning algorithms for binary classification. 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. A ...

In this example I will go through the implementation of the perceptron model in C++ so that you can get a better idea of how it works. First things first it is a good practice to write down a simple algorithm of what we want to do. Algorithm: Make a the vector for the weights and initialize it ...

What is the bias A perceptron can be seen as a function that maps an input (real-valued) vector x to an output value f(x) (binary value): where w is a vector of real-valued weights and b is a our bias value. The bias is a value that shifts the decision boundary away from the origin (0,0) and ...