## A Statistical Perspective on Knowledge Discovery in Databases (1996)

### Cached

### Download Links

- [www.datamininglab.com]
- [www.datamininglab.com]
- DBLP

### Other Repositories/Bibliography

Citations: | 41 - 0 self |

### BibTeX

@MISC{Elder96astatistical,

author = {John F. Elder and IV and Daryl Pregibon},

title = {A Statistical Perspective on Knowledge Discovery in Databases},

year = {1996}

}

### Years of Citing Articles

### OpenURL

### Abstract

The quest to find models usefully characterizing data is a process central to the scientific method, and has been carried out on many fronts. Researchers from an expanding number of fields have designed algorithms to discover rules or equations that capture key relationships between variables in a database. The task of this chapter is to provide a perspective on statistical techniques applicable to KDD; accordingly, we review below some major advances in statistics in the last few decades. We next highlight some distinctives of what may be called a "statistical viewpoint." Finally we overview some influential classical and modern statistical methods for practical model induction.