Sliced inverse regression with conditional entropy minimization

Hideitsu Hino, Keigo Wakayama, Noboru Murata

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    An appropriate dimension reduction of raw data helps to reduce computational time and to reveal the intrinsic structure of complex data. In this paper, a dimension reduction method for regression is proposed. The method is based on the well-known sliced inverse regression and conditional entropy minimization. Using entropy as a measure of dispersion of data distribution, dimension reduction subspace is estimated without assuming regression function form nor data distribution, unlike conventional sliced inverse regression. The proposed method is shown to perform well compared to some conventional methods through experiments using both artificial and real-world data sets.

    Original languageEnglish
    Title of host publicationProceedings - International Conference on Pattern Recognition
    Pages1185-1188
    Number of pages4
    Publication statusPublished - 2012
    Event21st International Conference on Pattern Recognition, ICPR 2012 - Tsukuba
    Duration: 2012 Nov 112012 Nov 15

    Other

    Other21st International Conference on Pattern Recognition, ICPR 2012
    CityTsukuba
    Period12/11/1112/11/15

    Fingerprint

    Entropy
    Experiments

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition

    Cite this

    Hino, H., Wakayama, K., & Murata, N. (2012). Sliced inverse regression with conditional entropy minimization. In Proceedings - International Conference on Pattern Recognition (pp. 1185-1188). [6460349]

    Sliced inverse regression with conditional entropy minimization. / Hino, Hideitsu; Wakayama, Keigo; Murata, Noboru.

    Proceedings - International Conference on Pattern Recognition. 2012. p. 1185-1188 6460349.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Hino, H, Wakayama, K & Murata, N 2012, Sliced inverse regression with conditional entropy minimization. in Proceedings - International Conference on Pattern Recognition., 6460349, pp. 1185-1188, 21st International Conference on Pattern Recognition, ICPR 2012, Tsukuba, 12/11/11.
    Hino H, Wakayama K, Murata N. Sliced inverse regression with conditional entropy minimization. In Proceedings - International Conference on Pattern Recognition. 2012. p. 1185-1188. 6460349
    Hino, Hideitsu ; Wakayama, Keigo ; Murata, Noboru. / Sliced inverse regression with conditional entropy minimization. Proceedings - International Conference on Pattern Recognition. 2012. pp. 1185-1188
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