Difference between revisions of "Perceptron (P)"
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** [[...predict categories]] | ** [[...predict categories]] | ||
* [[Capabilities]] | * [[Capabilities]] | ||
| − | * [[Deep Neural Network (DNN)]] | + | * [[Deep Neural Network (DNN)]] |
| + | ** [[Deep Neural Network (DNN)#Neural Network History|Neural Network History]] | ||
* [http://www.asimovinstitute.org/author/fjodorvanveen/ Neural Network Zoo | Fjodor Van Veen] | * [http://www.asimovinstitute.org/author/fjodorvanveen/ Neural Network Zoo | Fjodor Van Veen] | ||
* [http://en.wikipedia.org/wiki/Perceptron Wikipedia] | * [http://en.wikipedia.org/wiki/Perceptron Wikipedia] | ||
Revision as of 22:58, 31 March 2023
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A linear classifier (binary) helps to classify the given input data into two parts.
Two-Class Averaged Perceptron
The averaged perceptron method is an early and very simple version of a neural network. In this approach, inputs are classified into several possible outputs based on a linear function, and then combined with a set of weights that are derived from the feature vector—hence the name "perceptron."
