Noise detection in semi-supervised learning with the use of data streams

Noise detection in semi-supervised learning with the use of data streams

Often,  it  is  necessary  to  construct  training  sets.  If  we  have  only  a  small  number of tagged objects and a large group of unlabeled objects, we can build the training set simulating a data stream of unlabelled objects from which it is necessary to learn and to incorporate them to the t...

Full description

Bibliographic Details
Main Authors: Damaris Pascual González, Fernando D. Vázquez Mesa, J. Salvador Sánchez, Filiberto Pla
Format: Article
Language:English
Published: Universidad de Antioquia 2014-02-01
Series:Revista Facultad de Ingeniería Universidad de Antioquia
Subjects:
data streams
unlabeled data
noise cleaning
concept drift
Online Access:https://revistas.udea.edu.co/index.php/ingenieria/article/view/14514

Internet

https://revistas.udea.edu.co/index.php/ingenieria/article/view/14514

Similar Items