A Normalization Method for Contextual Data: Experience from a Large-scale Application

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TypeArticle
ConferenceProceedings of the 10th European Conference on Machine Learning (ECML-98), April 21-24, 1998., Chemnitz, Germany
AbstractThis paper describes a pre-processing technique to normalize contextually-dependent data before applying Machine Learning algorithms. Unlike many previous methods, our approach to normalization does not assume that the learning task is a classification task. We propose a data pre-processing algorithm which modifies the relevant attributes so that the effects of the contextual attributes on the relevant attributes are cancelled. These effects are modeled using a novel approach, based on the analysis of variance of the contextual attributes. The method is applied on a massive data repository in the area of aircraft maintenance.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number41559
NPARC number8914471
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Record identifier620e2bd5-1fd9-49a9-b19f-8e16e56c5e5f
Record created2009-04-22
Record modified2016-05-09
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