Unsupervised Classification of Mixed Data Type of Attributes Using Genetic Algorithm (Numeric, Categorical, Ordinal, Binary, Ratio-Scaled)

Author:

Rastogi Rohit,Agarwal Saumya,Sharma Palak,Kaul Uarvarshi,Jain Shilpi

Publisher

Springer India

Reference10 articles.

1. Li, J., Gao, X., Jiao, L.-C.: A GA-based clustering algorithm for large data sets with mixed numeric and categorical values. In: National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an

2. Huang, Z.: A fast clustering algorithm to cluster very large categorical data sets in data mining. In: Proceedings of the SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery, pp.1–8, Department of Computer Science, The University of British Columbia, Canada

3. Krovi, R.: Genetic Algorithm for Clustering: A Preliminary Investigation pp. 504–544. IEEE press, Piscataway (1991)

4. Huang, Z., Ng, M.K.: A fuzzy k-modes algorithm for clustering categorical data. IEEE Trans. Fuzzy Syst. 7(4), 446–452 (1999)

5. Christian, H., Liao, T.F.: How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification. In: University College London, UK and University of Illinois, Urbana–Champaign

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