A Statistical Perspective on Knowledge Discovery in Databases 4.1 Recent Statistical Contributions

The quest to nd models usefully characterizing data is a process central to the scientiic method, and has been carried out on many fronts. Researchers from an expanding number of elds 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 innuential classical and modern statistical methods for practical model induction. It would be unfortunate if the KDD community dismissed statistical methods on the basis of courses that they took on statistics several to many years ago. The following provides a rough chronology of \recent" signiicant contributions in statistics that are relevant to the KDD community. The noteworthy fact is that this time period coincides with the signiicant increases in computing horsepower and memory, powerful and expressive programming languages, and general accessibility to computing that has propelled us into