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Data stream classification with concept drift and extreme verification latency

Grant number: 14/12333-7
Support type:Scholarships in Brazil - Master
Effective date (Start): September 01, 2014
Effective date (End): July 31, 2016
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Cooperation agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
Principal Investigator:Gustavo Enrique de Almeida Prado Alves Batista
Grantee:Denis Moreira dos Reis
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated scholarship(s):15/01701-8 - Data stream analysis and evaluation under the presence of verification latency, BE.EP.MS

Abstract

Despite the relatively maturity of batch-mode supervised learning research, in which the data typifies stationary problems, many real world applications deal with data streams whose statistical properties change over time, causing what is known as concept drift. For such applications a large body of research has been done in the last years, with the objective of creating new models that are accurate even in the presence of concept drift. However, most of them assume that, once the classifier algorithm labels an event, its actual label become available. This project researches and shows solutions belonging to a new paradigm, where the unlabeled data is drifted back to its originally learned distribution. Such new paradigm allows an effective use of machine learning in the presence of concept drift, even when the actual labels are never available, keeping high performance both in accuracy and computational cost. Partial results serve as evidence of the viability of this paradigm. (AU)

Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
REIS, Denis Moreira dos. Data stream classification with concept drift and verification latency. 2016. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação São Carlos.

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