Ruta: implementations of neural autoencoders in R

Artículo de revista 2019

Autores: David Charte, Francisco Herrera Triguero, Francisco Charte Ojeda

Knowledge-Based SystemsVolumen 174Páginas 4-8

Cómo citar esta publicación

Charte, D. ", Herrera Triguero, F., & Charte Ojeda, F. (2019). Ruta: implementations of neural autoencoders in R. Knowledge-Based Systems, 174, 4-8. (Original work published 2019)
BibTeX

Resumen

Autoencoders are neural networks which perform feature learning on data. Many variants can be found in the literature, but their implementations are scarce, in separate software pieces and utilizing different languages and frameworks. The ruta package implements a unified foundation for the construction and training of autoencoders on top of Keras and Tensorflow, and allows for easy access to the main functionalities as well as full customization of their diverse aspects.

Detalles

Date Published
06/2019
Notas

TIN2015-68854-R,BigDaP-TOOLS