No study supervised machine learning based evolutionary multi-objective optimization View Homepage


Ontology type: schema:MonetaryGrant     


Grant Info

YEARS

2010-2012

FUNDING AMOUNT

180000 CNY

ABSTRACT

Machine learning based on a single evaluation criteria have been developed by leaps and bounds, but it is the nature of multi-objective optimization problem many machine learning problems. Evolutionary algorithms to solve multi-objective optimization problem has the potential advantages and achieved great success. The use of evolutionary multi-objective optimization problem to solve the problem of machine learning methods with multiple target characteristic, a plurality of evaluation criteria to explore the impact of machine learning. The problem with unsupervised machine learning methods, for example, in-depth study of the objective function of the impact mechanism and machine learning model selection mechanism, analyze and summarize the evolution of multi-target machine learning general rules and guidelines for algorithm design. The main contents include: the evolution of an efficient multi-objective optimization algorithm; multi-objective evolutionary clustering research; applied research in the field of telecommunications data mining multi-objective evolutionary machine learning algorithms; complex networks based on multi-objective framework Community Discovery and Evolution. This paper machine learning and evolutionary multi-objective optimization of these two research areas combined to multi-objective optimization evolutionary perspective study machine learning problems. Research on this subject can deepen our understanding of the mechanism and machine learning methods, while promoting evolutionary multi-objective optimization of research and development. More... »

URL

http://npd.nsfc.gov.cn/projectDetail.action?pid=60905025

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