Rectifier (neural networks)

Plot of the rectifier (blue) and softplus (green) functions near x = 0.

In the context of artificial neural networks, the rectifier is an activation function defined as

where x is the input to a neuron. This is also known as a ramp function, and it is analogous to half-wave rectification in electrical engineering. This activation function has been argued to be more biologically plausible than the widely used logistic sigmoid (which is inspired by probability theory; see logistic regression) and its more practical counterpart, the hyperbolic tangent. The rectifier is, as of 2015, the most popular activation function for deep neural networks.

单词	RELU
释义	RELU 英语百科 Rectifier (neural networks) In the context of artificial neural networks, the rectifier is an activation function defined as where x is the input to a neuron. This is also known as a ramp function, and it is analogous to half-wave rectification in electrical engineering. This activation function has been argued to be more biologically plausible than the widely used logistic sigmoid (which is inspired by probability theory; see logistic regression) and its more practical counterpart, the hyperbolic tangent. The rectifier is, as of 2015, the most popular activation function for deep neural networks.
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RELU

Rectifier (neural networks)