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LEAC: An efficient library for clustering with evolutionary algorithms
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DOI：10.1016/j.knosys.2019.05.008.png)
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This paper introduces LEAC, a new C++ partitioning clustering library based on evolutionary computation. LEAC provides plenty of elements (individual encoding schemes, genetic operators, evaluation metrics, among others) which allow an easy and fast development of new clustering algorithms. Furthermore, it includes 23 algorithms which represent the state-of-the-art in Evolutionary Algorithms for partial clustering. The paper describes through examples the main features and the design principles of the software, as well as how to use LEAC to carry out a comparison between different proposals and how to extend it by including new algorithms. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Clustering
C plus plus library
Evolutionary algorithms
Genetic algorithms
Software
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A survey on nature inspired metaheuristic algorithms for partitional clustering基于自然启发的分区聚类元启发式算法综述
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