TENSOR LOCALITY SENSITIVE DISCRIMINANT ANALYSIS AND ITS COMPLEXITY
Yantao Wei, Hong Li, Luoqing Li · International Journal of Wavelets Multiresolution and Information Processing · 2009
Feature extraction is one of the most challenging problems in pattern recognition fields and has attracted great attention recently. In this paper, we propose a novel feature extraction algorithm named tensor locality sensitive discriminant analysis which accepts tensors as inputs. The algorithm preserves the key structure of data by using the labeled samples and has high performance as well as low time complexity. Experiments on the three standard databases show that the proposed method has better performance and achieves high accuracy.