Discretization, continuous aspects, symbolisation, research
Abstract
Discretization is an important preprocessing technique used in many knowledge discovery and data mining tasks. Its main goal is to transform a set of continuous aspects into discrete ones, by associating categorical values to intervals and thus transforming numerical data into qualitative data. In this manner, symbolic data mining algorithms can be applied over continuous data and the representation of information is simplified, making it more brief and specific. This paper objective are to study terms and symbolisations related to discretization, a typical discretization process and discretization current status. We have also discussed the future research for discretization.
Article Details
Unique Paper ID: 143130
Publication Volume & Issue: Volume 2, Issue 7
Page(s): 641 - 645
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