Abstract
In this paper, semi-supervised classification concept is applied to Discriminant Analysis Feature Extraction (DAFE) and Nonparametric Weighted Feature Extraction (NWFE). The proposed semi-supervised DAFE and NWFE use the information of both labeled and unlabeled data in an iterative process. Experimental results of hyperspectral data show that the proposed feature extraction methods can improve the classification performance significantly with limited training samples.
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