Rotational Linear Discriminant Analysis Technique for Dimensionality Reduction
نویسندگان
چکیده
منابع مشابه
Rotational Linear Discriminant Analysis Using Bayes Rule for Dimensionality Reduction
Linear discriminant analysis (LDA) finds an orientation that projects high dimensional feature vectors to reduced dimensional feature space in such a way that the overlapping between the classes in this feature space is minimum. This overlapping is usually finite and produces finite classification error which is further minimized by rotational LDA technique. This rotational LDA technique rotate...
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ژورنال
عنوان ژورنال: IEEE Transactions on Knowledge and Data Engineering
سال: 2008
ISSN: 1041-4347
DOI: 10.1109/tkde.2008.101