“Intelligent Yardstick”, an Approach of Ranking to Filter Non-promising Attributes from Schema in Data Mining Process
DOI: 10.1007/978-3-540-37256-1_79
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摘要: Knowledge searching and representation process needs to go through filtering make it concise precise. The data mining (DM) as a knowledge extraction method also remove unnecessary or erroneous data. Sometimes cover processing representational limits, especially in visual mining. Common approaches for shrinking the database are — discard records, prune attributes from reduce dimensionality. In this paper we propose an approach where have applied single dimension DM on each individual attribute select only those which good future full-scale non prospective attributes. check several properties of like distance, clustering tendency cluster density. According result, formulate scale that will rank all indicate their importance schema. main observation helps us build is —‘An has no pattern itself not help find multidimensional environment’.
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