L' interest growing for l' exploration of data is justified by a common problem in all the disciplines: how can one store, consult, the model, and, finally, to describe and include/understand the very important whole of data? Historically, various aspects of l' exploration of data were treated independently by the various disciplines. It s' acts of the first truly interdisciplinary text on dated mining, mixing the contributions with sciences of l' information, l' data processing and of the statistics. The book is composed of three sections. The first, foundations, give an outline tutoriel the principles governing the algorithms d' exploration of data and their application. The presentation puts l' accent on l' intuition rather than of rigour. The second section, the algorithms d' extraction of data, shows how the algorithms are built so as to solve the specific problems in a reasoned way. Algorithms covered of the trees and the rules of classification and regression, rules d' association, networks of the belief, the traditional one of the statistical, model models nonlinear such as the neural networks, and local " containing mémoire" models. The third part shows how l' together of l' preceding s' analyzes; encase lorsqu' one l' applies to problems of real data of l' mining. The subjects include the role of the metadata, how to manage the missing data and pretreatment of the data.
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