Logitboost extension for early classification of sequences

Authors:
Tomoyuki Fujino;Katsuhiko Ishiguro;Hiroshi Sawada
Affiliations:
Graduate School of Science and Technology, Keio University;NTT Communication Science Laboratories;NTT Communication Science Laboratories
Venue:
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Year:
2011

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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 Adaboostbased "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.