ML Anthology

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

Sylvain Létourneau, Stan Matwin, Fazel Famili
ECML-PKDD 1998 pp. 49-54
doi:10.1007/BFB0026671 /ecmlpkdd/1998/letourneau1998ecml-normalization/

Abstract

This 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.

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Cite

Text

Létourneau et al. "A Normalization Method for Contextual Data: Experience from a Large-Scale Application." European Conference on Machine Learning, 1998. doi:10.1007/BFB0026671

Markdown

[Létourneau et al. "A Normalization Method for Contextual Data: Experience from a Large-Scale Application." European Conference on Machine Learning, 1998.](https://mlanthology.org/ecmlpkdd/1998/letourneau1998ecml-normalization/) doi:10.1007/BFB0026671

BibTeX

@inproceedings{letourneau1998ecml-normalization,
  title     = {{A Normalization Method for Contextual Data: Experience from a Large-Scale Application}},
  author    = {Létourneau, Sylvain and Matwin, Stan and Famili, Fazel},
  booktitle = {European Conference on Machine Learning},
  year      = {1998},
  pages     = {49-54},
  doi       = {10.1007/BFB0026671},
  url       = {https://mlanthology.org/ecmlpkdd/1998/letourneau1998ecml-normalization/}
}