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An optimal linear time algorithm for quasi-monotonic segmentation

By Daniel Lemire

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.

Year: 2005
OAI identifier: oai:CiteSeerX.psu:10.1.1.135.1747
Provided by: CiteSeerX
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