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Automated Anomaly Detection

Automated Anomaly Detection

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Author(s): Brad Morantz (Georgia State University, USA)
Copyright: 2005
Pages: 5
Source title: Encyclopedia of Data Warehousing and Mining
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59140-557-3.ch016

Keywords: Data Mining and Databases / Data Warehousing / Information Science Reference / Library & Information Science

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Abstract

Preparing a dataset is a very important step in data mining. If the input to the process contains problems, noise, or errors, then the results will reflect this, as well. Not all possible combinations of the data should exist, as the data represent real-world observations. Correlation is expected among the variables. If all possible combinations were represented, then there would be no knowledge to be gained from the mining process.

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