Introduction to Perceptron

What is a perceptron?

Perceptron is a binary linear classifier used in supervised learning to classify the given input data.

Visualize a perceptron

In the case of two input data points, the perceptron model makes a line that separates the two classes.

Boundary

The boundary line that separates the two classes are:

$$w_1x_1 + w_2x_2 + b = 0$$

Here:

• $x_1$ and $x_2$ are the inputs
• $w_1$ and $w_2$ are the weights
• $b$ is the bias

Prediction

The predicted value on applying the step function is given by:

$\hat{y}$=$\Bigg\{$ $\begin{matrix} 1 & {if\; w_1x_1 +w_2x_2 + b >= 0}\\ \\ 0 & otherwise \end{matrix}$

In the case of three input data points, the perceptron model would separate the two classes using a plane:

Boundary

The plane separating the data points would be:

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