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- Delta_rule abstract "In machine learning, the delta rule is a gradient descent learning rule for updating the weights of the inputs to artificial neurons in single-layer neural network. It is a special case of the more general backpropagation algorithm. For a neuron with activation function , the delta rule for 's th weight is given by,whereIt holds that and .The delta rule is commonly stated in simplified form for a neuron with a linear activation function as While the delta rule is similar to the perceptron's update rule, the derivation is different. The perceptron uses the Heaviside step function as the activation function , and that means that does not exist at zero, and is equal to zero elsewhere, which makes the direct application of the delta rule impossible.".
- Delta_rule wikiPageID "1237612".
- Delta_rule wikiPageRevisionID "606423176".
- Delta_rule hasPhotoCollection Delta_rule.
- Delta_rule subject Category:Neural_networks.
- Delta_rule type Abstraction100002137.
- Delta_rule type Communication100033020.
- Delta_rule type ComputerArchitecture106725249.
- Delta_rule type Description106724763.
- Delta_rule type Message106598915.
- Delta_rule type NeuralNetwork106725467.
- Delta_rule type NeuralNetworks.
- Delta_rule type Specification106725067.
- Delta_rule type Statement106722453.
- Delta_rule comment "In machine learning, the delta rule is a gradient descent learning rule for updating the weights of the inputs to artificial neurons in single-layer neural network. It is a special case of the more general backpropagation algorithm.".
- Delta_rule label "Delta rule".
- Delta_rule label "Regola delta".
- Delta_rule label "Дельта-правило".
- Delta_rule sameAs Regola_delta.
- Delta_rule sameAs m.04l2pf.
- Delta_rule sameAs Q577075.
- Delta_rule sameAs Q577075.
- Delta_rule sameAs Delta_rule.
- Delta_rule wasDerivedFrom Delta_rule?oldid=606423176.
- Delta_rule isPrimaryTopicOf Delta_rule.