Alzheimer's disease data set visualised
Alzheimer's Disease project
This project aims to investigate on the feature selection and dimensionality reduction on Alzheimer’s Disease and other biomedical data using rough-fuzzy hybridization, rough-GA approaches, and NSC (Nearest Shrunken Centroid) approaches. Also this project is focussed on not only bio-markers discovery with minimal number of most significant attributes, but also robust classification methodologies on such high dimensional biomedical data sets. Other data sets used in this project are colon and leukaemia cancer data.