Differential Evolution Based Classification with Pool of Distances and Aggregation Operators
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Date
2015
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Lappeenranta University of Technology
Abstract
The objective of this thesis is to develop and generalize further the differential evolution
based data classification method. For many years, evolutionary algorithms have been
successfully applied to many classification tasks. Evolution algorithms are population based,
stochastic search algorithms that mimic natural selection and genetics. Differential evolution
is an evolutionary algorithm that has gained popularity because of its simplicity and good
observed performance. In this thesis a differential evolution classifier with pool of ...
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Citation
Koloseni, D., 2015. Differential evolution based classification with pool of distances and aggregation operators. Acta Universitatis Lappeenrantaensis.