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Strength in diversity - the advance of data analysis (English)
| Description: |
Although the origins can be traced back as far as one likes, the proper scientific analysis of data is really only around a century old. For most of that century, data analysis was the realm of only one discipline - statistics. In recent decades, however, as a consequence of the development of the computer, things have changed dramatically and now there are several such disciplines, including machine learning, pattern recognition, and data mining. Although all of these disciplines are concerned with extracting information from data, they have subtle differences in aims and emphasis. This paper looks at some of the similarities and some of the differences, noting where the disciplines intersect and, perhaps of more interest, where they do not. Particular issues examined include the nature of the data with which they are concerned, the role of mathematics, differences in the objectives, how the different areas of application have led to different aims, and how the different disciplines have led sometimes to the same analytic tools being developed, but also sometimes to different tools being developed. Some conjectures about likely future developments are given. |
| Lecturer: |
Hand, David J.
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| Language: |
English |
| URL: |
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| Matrial: |
Hand.pdf (318 KB) |
| Date: |
2004
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| Address: |
ECML/PKDD2004
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