Pruning is the practice of removing

parameter A parameter (), generally, is any characteristic that can help in defining or classifying a particular system (meaning an event, project, object, situation, etc.). That is, a parameter is an element of a system that is useful, or critical, when ...

s (which may entail removing individual parameters, or parameters in groups such as by

neurons A neuron, neurone, or nerve cell is an electrically excitable cell that communicates with other cells via specialized connections called synapses. The neuron is the main component of nervous tissue in all animals except sponges and placozoa. ...

) from an existing artificial neural networks. The goal of this process is to maintain accuracy of the network while increasing its efficiency. This can be done to reduce the

computational resource In computational complexity theory, a computational resource is a resource used by some computational models in the solution of computational problems. The simplest computational resources are computation time, the number of steps necessary to s ...

s required to run the neural network. A biological process of

synaptic pruning Synaptic pruning, a phase in the development of the nervous system, is the process of synapse elimination that occurs between early childhood and the onset of puberty in many mammals, including humans. Pruning starts near the time of birth and co ...

takes place in the brain of mammals during development (see also

Neural Darwinism Neural Darwinism is a biological, and more specifically Darwinian and selectionist, approach to understanding global brain function, originally proposed by American biologist, researcher and Nobel-Prize recipient Gerald Maurice Edelman (July 1, ...

Node (neuron) pruning

A basic algorithm for pruning is as follows: #Evaluate the importance of each neuron. #Rank the neurons according to their importance (assuming there is a clearly defined measure for "importance"). #Remove the least important neuron. #Check a termination condition (to be determined by the user) to see whether to continue pruning.

Edge (weight) pruning

Most work on neural network pruning focuses on removing weights, namely, setting their values to zero. Early work suggested to also change the values of non-pruned weights.

References

Artificial neural networks {{Compu-ai-stub