Parsimonious Mahalanobis kernel for the classification of high dimensional data
نویسندگان
چکیده
منابع مشابه
Parsimonious Mahalanobis kernel for the classification of high dimensional data
The classification of high dimensional data with kernel methods is considered in this article. Exploiting the emptiness property of high dimensional spaces, a kernel based on the Mahalanobis distance is proposed. The computation of the Mahalanobis distance requires the inversion of a covariance matrix. In high dimensional spaces, the estimated covariance matrix is ill-conditioned and its invers...
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ژورنال
عنوان ژورنال: Pattern Recognition
سال: 2013
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2012.09.009