Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
ACM Computing Surveys (CSUR)
Machine Learning
Knowledge Discovery in Databases
Knowledge Discovery in Databases
An Evolutionary Immune Network for Data Clustering
SBRN '00 Proceedings of the VI Brazilian Symposium on Neural Networks (SBRN'00)
A method for personalized clustering in data intensive web applications
Proceedings of the joint international workshop on Adaptivity, personalization & the semantic web
A genetic rule-based data clustering toolkit
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Clustering techniques utilized in web usage mining
AIKED'06 Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases
Alternative adaptive fuzzy C-means clustering
EC'06 Proceedings of the 7th WSEAS International Conference on Evolutionary Computing
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Data mining is the process of deriving knowledge from data. The data clustering is a classical activity in data mining. Clustering is the process of grouping objects together in such a way that the objects belonging to the same group are similar and those belonging to different groups are dissimilar. In this paper we propose a method to carry out data clustering using Evolutionary Computation. We use evolutionary characteristics to define the data clustering procedure. In addition, we present an example of application of our approach, the definition of healthcare centers for a given Venezuelan region.