High-dimensional data
نویسندگان
چکیده
منابع مشابه
Methods for regression analysis in high-dimensional data
By evolving science, knowledge and technology, new and precise methods for measuring, collecting and recording information have been innovated, which have resulted in the appearance and development of high-dimensional data. The high-dimensional data set, i.e., a data set in which the number of explanatory variables is much larger than the number of observations, cannot be easily analyzed by ...
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Observations from real-world problems are often highdimensional vectors, i.e. made up of many variables. Learning methods, including artificial neural networks, often have difficulties to handle a relatively small number of high-dimensional data. In this paper, we show how concepts gained from our intuition on 2and 3dimensional data can be misleading when used in high-dimensional settings. When...
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Clustering in high-dimensional spaces is a difficult problem which is recurrent in many domains, for example in image analysis. The difficulty is due to the fact that highdimensional data usually live in different low-dimensional subspaces hidden in the original space. This paper presents a family of Gaussian mixture models designed for highdimensional data which combine the ideas of subspace c...
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ژورنال
عنوان ژورنال: Journal of the National Science Foundation of Sri Lanka
سال: 2016
ISSN: 2362-0161,1391-4588
DOI: 10.4038/jnsfsr.v44i1.7976