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arxiv: 0806.2669 · v1 · submitted 2008-06-16 · 📊 stat.ML

Local Procrustes for Manifold Embedding: A Measure of Embedding Quality and Embedding Algorithms

classification 📊 stat.ML
keywords measurealgorithmsembeddingprocrustesdimension-reductionexistingnoveloutput
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We present the Procrustes measure, a novel measure based on Procrustes rotation that enables quantitative comparison of the output of manifold-based embedding algorithms (such as LLE (Roweis and Saul, 2000) and Isomap (Tenenbaum et al, 2000)). The measure also serves as a natural tool when choosing dimension-reduction parameters. We also present two novel dimension-reduction techniques that attempt to minimize the suggested measure, and compare the results of these techniques to the results of existing algorithms. Finally, we suggest a simple iterative method that can be used to improve the output of existing algorithms.

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