Clustering Algorithms for High Dimensional Data - A Survey of Issues and Existing Approaches

Provided by: Interscience Open Access Journals
Topic: Data Management
Format: PDF
Clustering is the most prominent data mining technique used for grouping the data into clusters based on distance measures. With the advent growth of high dimensional data such as microarray gene expression data, and grouping high dimensional data into clusters will encounter the similarity between the objects in the full dimensional space is often invalid because it contains different types of data. The process of grouping into high dimensional data into clusters is not accurate and perhaps not up to the level of expectation when the dimension of the dataset is high.

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