Clustering Numerical and Categorical Data

نویسنده

  • Ricardo Linden
چکیده

Clustering is an important technique for data mining which allows us to discover unknown relationships in our data sets. Clustering algorithms that use metrics based on the natural ordering of numbers cannot be applied to categorical (non-numerical) data. In this tutorial we will review the main methods for numerical data clustering (K-Means, Hierarchical Clustering and Fuzzy CMeans) and then study two methods for categorical data clustering: CLICK (based on graphs) and STIRR (based on dynamical systems).

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تاریخ انتشار 2004