Abstract:Dimension reduction is often used for several procedures of analysis of high dimensional biomedical data-sets such as classification or outlier detection. To improve performance of such data-mining steps, preserving both distance information and local topology among data-points could be more useful than giving priority to visualisation in low dimension. Therefore, we introduce topology preserving distance scaling (TPDS) to augment dimension reduction method meant to reproduce distance information in higher dim… Show more
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