Automatic Configuration of Spectral Dimensionality
نویسندگان
چکیده
5 We propose an advanced framework for the automatic configuration of 6 spectral dimensionality reduction methods. This is achieved by introducing, 7 first, the mutual information measure to assess the quality of discovered 8 embedded spaces. Secondly, unsupervised Radial Basis Function network is 9 designated for mapping between spaces where the learning process is derived 10 from graph theory and based on Markov cluster algorithm. Experiments 11 on synthetic and real datasets demonstrate the effectiveness of the proposed 12 methodology. 13
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