Reduction of High Dimensional Data Using Discriminant Analysis Methods

E. Aigbokhan E., O. Alakiri H., N. Lawal O.
2019 Zenodo  
In recent years, analysis of high dimensional data for several applications such as content based retrieval, speech signals, fMRI scans, electrocardiogram signal analysis, multimedia retrieval, market based applications etc. has become a major problem. To overcome this challenge, dimensionality reduction techniques, which enable high dimensional data to be represented in a low dimensional space have been developed and deployed for varieties of application to fast track the study of the
more » ... on structure. In this paper, a comparative study of LDA and a KDA among the dimensionality reduction techniques were considered using data samples collected from survey and it was implemented using object oriented programming language (C#). The results reveal that less data components were discovered by LDA across the different dataset tested in comparison with KDA.
doi:10.5281/zenodo.2844614 fatcat:6wot3mujlvep7alznybkkgz2qu