Data Modeling
Abstract
Creating and deploying a data model is the last step of the data mining process, having already defined a good business objective; extracted and prepared the data; guaranteed its quality; and analyzed, segmented, and created new indicators and factors with greater information value. This chapter defines what is meant by a data model and introduces key associated concepts such as supervised and unsupervised learning, cross-validation, and how to evaluate the precision of the modeling results. A variety of techniques for modeling data are considered, from AI (Artificial Intelligence) approaches, such as neural networks and rule induction, to statistical techniques such as regression. The chapter goes on to discuss ...
Get Commercial Data Mining now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
