JFAS_Vol 10 N 02

Permanent URI for this collectionhttps://archives.univ-eloued.dz/handle/123456789/10263

Browse

Browsing JFAS_Vol 10 N 02 by Subject "Data mining, survey, Transfer learning, Traditional machine learning"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • No Thumbnail Available
    Item
    IMPROVE A LEARNER: A SURVEY OF TRANSFER LEARNING
    (جامعة الوادي university of eloued, 2018-05-01) A., S. Bais
    Transfer learning is a subclass of machine learning, which uses training data (source), drawn from a diverse domain than that of the testing data (target). The real world is messy and contains an infinite range of novel eventualities. Transfer learning across different feature spaces is usually a tougher problem than Transfer Learning within the common feature space. This survey paper defines transfer learning to feature representation that maps the target domain to the source domains exploiting a set of meticulously manufactured features and applications to transfer learning. This paper systematically examines a feature based transfer techniques and reviews some current analysis on the topic of negative transfer