Abstract
In this research an N-Dimentional clustering algorithm based on ACE algorithm for large datasets is described. Each part of the algorithm will be explained and experimental results obtained from apply this algorithm are discussed. The research is focused on the fast and accurate clustering using real databases as workspace instead of directly loaded data into memory since this is very limited and insufficient when large data amount are used. This algorithm can be applied to a great variety and types of information i.e. geospatial data, medical data, biological data and others. The number of computations required by the algorithm is ~O(N).
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Gil, M., Ochoa, A., Zamarrón, A., Carpio, J. (2009). Hybrid Algorithm to Data Clustering. In: Corchado, E., Wu, X., Oja, E., Herrero, Á., Baruque, B. (eds) Hybrid Artificial Intelligence Systems. HAIS 2009. Lecture Notes in Computer Science(), vol 5572. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02319-4_82
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DOI: https://doi.org/10.1007/978-3-642-02319-4_82
Publisher Name: Springer, Berlin, Heidelberg
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