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Times Series Classification Using Different Data Representations and Ensembles

Grant number: 12/08923-8
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): August 01, 2012
Effective date (End): January 31, 2017
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal researcher:Gustavo Enrique de Almeida Prado Alves Batista
Grantee:Rafael Giusti
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

There is an increasing interest in techniques for analysis of time-related data in the last decades. Such interest is explained by the fact that nearly all human activities produce time-related data. In this project, we aim at developing time series classification algorithms. Although a great deal of classification algorithms has been proposed in the last few decades, experimental evaluation suggests that a simple K-nearest neighbour classifier outperforms more complex classifiers in a wide range of application domains.One currently open question is how one can improve the performance of the K-nearest neighbours classifier for application domains in which this technique typically underperforms. The main hypothesis of this research work is that a simple yet effective change of data representation may provide a meaningful improvement on the classification performance. Our goal is to investigate new, effective time series data representations and propose distance measures that are effective for such representations.

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
SILVA, DIEGO F.; GIUSTI, RAFAEL; KEOGH, EAMONN; BATISTA, GUSTAVO E. A. P. A.. Speeding up similarity search under dynamic time warping by pruning unpromising alignments. DATA MINING AND KNOWLEDGE DISCOVERY, v. 32, n. 4, p. 988-1016, . (12/08923-8, 13/26151-5, 16/04986-6)
Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
GIUSTI, Rafael. Time series classification using multiple representations and ensembles. 2017. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.