A Cooperative Biomimetic Approach for High Dimensional Data Mining

International audienceWe propose in this paper an original alternative to solve the problem of search space visualization to discover the complex structure of data, while respecting topology. Our cooperative approach provided a multi-dimensional visual-ization from the data. The first method is the subspace selection from whole data space. This selection is obtained by a genetic algorithm reducing the data dimension space by simply determining the most relevant dimensions evaluated by a distribution measure. Once a subspace selected we construct a neighborhood graph using artificial ants algorithm