Abstract
Each manifold learning algorithm has its own advantages and applicable situations. And it is an important question that how to select out the best one as the result. To this end, a manifold learning fusion algorithm is proposed to select out the best one from multiple results yielded by different manifold learning algorithms according to an equation of criterion. Moreover, a kind of local optimal technique is used to optimize the embedded result. By combining the advantages of classical manifold learning algorithms that preserve some properties effectively and the better preservation to distance and angle, our algorithm can yield a more satisfactory result to almost all kind of manifolds. The effectiveness and stability of our algorithm are further confirmed by some experiments.
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Gu, Y., Zhang, D., Ma, Z., Niu, G. (2014). A Manifold Learning Fusion Algorithm Based on Distance and Angle Preservation. In: Li, S., Liu, C., Wang, Y. (eds) Pattern Recognition. CCPR 2014. Communications in Computer and Information Science, vol 483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45646-0_4
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DOI: https://doi.org/10.1007/978-3-662-45646-0_4
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