Abstract
Visualization methods do not scale well with high number of features. We present an approach using a consensus theory based feature selection (CTBFS) algorithm, clustering for sampling and visualization for weight assignment in order to aggregate multivariate and multidimensional datasets. We use datasets available in UCI and Kent Ridge Bio Medical Dataset Repositories in order to evaluate the performance of our new approach.
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