ℓ1 Major Component Detection and Analysis (ℓ1 MCDA): Foundations in Two Dimensions
نویسندگان
چکیده
منابع مشابه
ℓ1 Major Component Detection and Analysis (ℓ1 MCDA): Foundations in Two Dimensions
Principal Component Analysis (PCA) is widely used for identifying the major components of statistically distributed point clouds. Robust versions of PCA, often based in part on the l norm (rather than the l norm), are increasingly used, especially for point clouds with many outliers. Neither standard PCA nor robust PCAs can provide, without additional assumptions, reliable information for outli...
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ژورنال
عنوان ژورنال: Algorithms
سال: 2013
ISSN: 1999-4893
DOI: 10.3390/a6010012