perceptron
(To be removed) Simple single-layer binary classifier
perceptron will be removed in a future release. For more information,
see Transition Legacy Neural Network Code to dlnetwork Workflows.
For advice on updating your code, see Version History.
Description
Note
Deep Learning Toolbox™ supports perceptrons for historical interest. For better
results, you should instead use patternnet, which can
solve nonlinearly separable problems. Sometimes the term “perceptrons”
refers to feedforward pattern recognition networks; but the original
perceptron, described here, can solve only simple problems.
perceptron(
takes a hard limit transfer function, hardlimitTF,perceptronLF)hardlimitTF, and a
perceptron learning rule, perceptronLF, and returns a
perceptron.
In addition to the default hard limit transfer function, perceptrons can be
created with the hardlims transfer function. The other option
for the perceptron learning rule is learnpn.
Perceptrons are simple single-layer binary classifiers, which divide the input space with a linear decision boundary.
Perceptrons can learn to solve a narrow range of classification problems. They were one of the first neural networks to reliably solve a given class of problem, and their advantage is a simple learning rule.
Examples
Input Arguments
Version History
Introduced in R2010bSee Also
Time Series
Modeler | fitrnet (Statistics and Machine Learning Toolbox) | fitcnet (Statistics and Machine Learning Toolbox) | trainnet | trainingOptions | dlnetwork

