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Neighborhood Dependencies for Prediction

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Advances in Knowledge Discovery and Data Mining (PAKDD 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2035))

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Abstract

We introduce the construct of neighborhood dependency (ND) to express regularities like: “Families with similar size and income, tend to own cars of similar size.” Arguably, the discovery of such regularities is useful for prediction purposes. We have implemented and tested an algorithm for mining NDs. The discovered NDs are then used in the P-neighborhood method to predict unknown values.

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© 2001 Springer-Verlag Berlin Heidelberg

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Bassée, R., Wijsen, J. (2001). Neighborhood Dependencies for Prediction. In: Cheung, D., Williams, G.J., Li, Q. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2001. Lecture Notes in Computer Science(), vol 2035. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45357-1_59

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  • DOI: https://doi.org/10.1007/3-540-45357-1_59

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41910-5

  • Online ISBN: 978-3-540-45357-4

  • eBook Packages: Springer Book Archive

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