On data mining,compression, and Kolmogorov complexity |
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| Authors: | Christos Faloutsos Vasileios Megalooikonomou |
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| Affiliation: | (1) School of Computer Science, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213-3891, USA;(2) Department of Computer and Information Sciences, Temple University, 314 Wachman Hall, 1805 N. Broad Street, Philadelphia, PA 19122, USA |
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| Abstract: | Will we ever have a theory of data mining analogous to the relational algebra in databases? Why do we have so many clearly different clustering algorithms? Could data mining be automated? We show that the answer to all these questions is negative, because data mining is closely related to compression and Kolmogorov complexity; and the latter is undecidable. Therefore, data mining will always be an art, where our goal will be to find better models (patterns) that fit our datasets as best as possible. |
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| Keywords: | Data mining Compression Kolmogorov complexity Clustering Classification Forecasting Outliers |
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