A Nonlinear Dimensionality Reduction Using Combined Approach to Feature Space Decomposition
نویسنده
چکیده
In this paper we propose a new combined approach to feature space decomposition to improve the efficiency of the nonlinear dimensionality reduction method. The approach performs the decomposition of the original multidimensional space, taking into account the configuration of objects in the target low-dimensional space. The proposed approach is compared to the approach using hierarchical clustering in the original space and to the approach based on the decomposition of the target space using KD-Tree.
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