Dimensionality Reduction Evolution and Validation
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2015, Vol 17, Issue 3
Abstract
Abstract: In this paper, proposing visualized and quantitative evaluation methods for validation dimensionalityreduction techniques performance. Four well known techniques for dimensionality reduction evaluated, verifythe capacity of generating a lower dimensional chemical space with minimum information error. Real chemicaldatabase used to generate a sample with specific structure as an input to evolution process. The evaluation isperformed in two ways: first visually checking the sample structure, second measuring the local and globaldistance based error rate that are trained on the low-dimensional data representation. All the evaluation havebeen done for the four dimensional reduction techniques then result shows weather “trustable” to techniquethat likely preserves properties with low generalization error and “Un-trustable” which does not preserve theproperties.
Authors and Affiliations
Mohammed Hussein Shukur
Keywords
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