Using phidelta diagrams to discover relevant patterns in multilayer perceptrons
Abstract Understanding the inner behaviour of multilayer perceptrons during and after training is a goal of paramount importance for many researchers worldwide. This article experimentally shows that relevant patterns emerge upon training, which are typically related to the underlying problem diffic...
Enregistré dans:
Auteur principal: | Giuliano Armano |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2020
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/23b3497c05374c0a8f955325aa4f0c7d |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Classification of patients with Alzheimer’s disease using the arterial pulse spectrum and a multilayer-perceptron analysis
par: Shun-Ku Lin, et autres
Publié: (2021) -
High-frequency conductivity at Larmor-frequency in human brain using moving local window multilayer perceptron neural network.
par: Mun Bae Lee, et autres
Publié: (2021) -
Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits
par: F. Merrikh Bayat, et autres
Publié: (2018) -
Modeling of Soil Compaction Beneath the Tractor Tire using Multilayer Perceptron Neural Networks
par: Gh Shahgholi, et autres
Publié: (2018) -
Development of the classifier based on a multilayer perceptron using genetic algorithm and cart decision tree
par: Lyudmila Dobrovska, et autres
Publié: (2021)