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Evolutionary Intelligence

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02-02-2019 | Review Article

Incremental supervised learning: algorithms and applications in pattern recognition

Author: Aida Chefrour

Published in: Evolutionary Intelligence | Issue 2/2019

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Abstract

The most effective well-known methods in the context of static machine learning offer no alternative to evolution and dynamic adaptation to integrate new data or to restructure problems already partially learned. In this area, the incremental learning represents an interesting alternative and constitutes an open research field, becoming one of the major concerns of the machine learning and classification community. In this paper, we study incremental supervised learning techniques and their applications, especially in the field of pattern recognition. This article presents an overview of the main concepts and supervised algorithms of incremental learning, including a synthesis of research studies done in this field and focusing on neural networks, decision trees and support vector machines.

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Title: Incremental supervised learning: algorithms and applications in pattern recognition
Author: Aida Chefrour
Publication date: 02-02-2019
Publisher: Springer Berlin Heidelberg
Published in: Evolutionary Intelligence / Issue 2/2019
Print ISSN: 1864-5909
Electronic ISSN: 1864-5917
DOI: https://doi.org/10.1007/s12065-019-00203-y

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