Squashing flat files flatter
- 1 August 1999
- proceedings article
- Published by Association for Computing Machinery (ACM)
Abstract
A feature of data mining that distinguishes it from "classical" machine learning (ML) and statistical modeling (SM) is scale. The community seems to agree on this yet progress to this point has been limited. We present a methodology that addresses scale in a novel fashion that has the potential for revolutionizing the field. While the methodology applies most directly to flat (row by column) data sets we believe that it can be adapted to other representations. Our approach to the problem is not ...Keywords
This publication has 1 reference indexed in Scilit:
- BIRCH: A New Data Clustering Algorithm and Its ApplicationsData Mining and Knowledge Discovery, 1997