Lemire, Brooks and Yan (2005) An Optimal Linear Time Algorithm for Quasi-Monotonic Segmentation

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An Optimal Linear Time Algorithm for Quasi-Monotonic Segmentation

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CONTRIBUTORS:

	Author:	Lemire, Daniel (Université du Québec à Montréal (UQAM))
	Author:	Brooks, Martin
	Author:	Yan, Yuhong

PROCEEDINGS TITLE:

IEEE Data Mining 2005 (ICDM-05)

YEAR:

2005

PUB TYPE:

Conference Paper in Proceedings

PAGES:

n/a - n/a

SUBJECT(S):

Piecewise Quasi-Monotone Functions, Segmentation, ECG, Spline

DISCIPLINE:

Computer Science

HTTP:

http://www.daniel-lemire.com/fr/abstracts/ICDM05.html

LANGUAGE:

English

PUB ID:

103-419-650 (Last edited on 2005/09/06 10:27:50 GMT-6)

SPONSOR(S):

ABSTRACT:
Monotonicity is a simple yet significant qualitative characteristic. We consider the problem of segmenting an array in up to K segments. We want segments to be as monotonic as possible and to alternate signs. We propose a quality metric for this problem, present an optimal linear time algorithm based on novel formalism, and compare experimentally its performance to a linear time top-down regression algorithm. We show that our algorithm is faster and more accurate. Applications include pattern recognition and qualitative modeling.

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