Perceptron and BP neural network

First, Perceptron

1. The perception of the concept machine

Is a linear perceptron model for binary classification, the input feature vector is an example of the output is an example of a category, the category two values ​​take +1 and -1, + 1 represents a positive type, -1 for negative type. Space corresponding to the input perceptron (feature space) in the example divided into two positive and negative hyperplane, belonging to the discriminant model. Perceptron learning algorithm is simple and easy to implement, and is divided into the original form of the dual form.