A dimensionality reduction method of continuous dependent variables based supervised Laplacian eigenmaps
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DOI: 10.1080/00949655.2019.1607347
Abstract: ABSTRACT Dimensionality reduction is one of the important preprocessing steps in high-dimensional data analysis. In this paper we propose a supervised manifold learning method, it makes use of the information of continuous dependent variables to… read more here.
Keywords: continuous dependent; dependent variables; dimensionality reduction; laplacian eigenmaps ... See more keywords