CORDIS Project
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This project focuses on improving pattern recognition methods for high-dimensional data, which is common in fields like finance and neuroimaging. It aims to develop techniques that reduce dimensionality while maintaining relevant information, enabling more effective data analysis.
High dimensional data, where the number of variables is larger than the sample size, are encountered in a wide range of areas such as microarray studies, finance, engineering, biometrics and neuroimaging.
This project is on pattern recognition (classification and clustering) of high dimensional data.
Statistical methodology (including recognition methods) available for analyzing such data suffers from the curse of dimensionality as the enormous number of variables poses challenges to conventiona…
KOC UNIVERSITY
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