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Practical Introduction to Clustering Data | | Alexander K. Hartmann
; | | Date: |
16 Feb 2016 | | Abstract: | Data clustering is an approach to seek for structure in sets of complex data,
i.e., sets of "objects". The main objective is to identify groups of objects
which are similar to each other, e.g., for classification. Here, an
introduction to clustering is given and three basic approaches are introduced:
the k-means algorithm, neighbour-based clustering, and an agglomerative
clustering method. For all cases, C source code examples are given, allowing
for an easy implementation. | | Source: | arXiv, 1602.5124 | | Services: | Forum | Review | PDF | Favorites | |
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