Logitboost extension for early classification of sequences

0Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

We propose a new boosting method for classification of time sequences. In the problem of on-line classification, it is essential to classify time sequences as quickly as possible in many practical cases. This type of classification is called "early classification." Recently, an Adaboost-based "Earlyboost" has been proposed, which is known for its efficiency. In this paper, we propose a Logitboost-based early classification for further improvements of Earlyboost. We demonstrate the structure of the proposed method, and experimentally verify its performance. © 2011 Springer-Verlag.

Cite

CITATION STYLE

APA

Fujino, T., Ishiguro, K., & Sawada, H. (2011). Logitboost extension for early classification of sequences. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6854 LNCS, pp. 579–588). https://doi.org/10.1007/978-3-642-23672-3_70

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free