An Improved ISOMAP for Visualization and Classification of Multiple Manifolds

  title={An Improved ISOMAP for Visualization and Classification of Multiple Manifolds},
  author={Hong-yuan Wang and Xiucai Ding and Qi-Cai Cheng and Fuhua Chen},
The classical algorithm ISOMAP can find the intrinsic low-dimensional structures hidden in high-dimensional data uniformly distributed on or around a single manifold. But if the data are sampled from multi-class, each of which corresponds to an independent manifold, and clusters formed by data points belonging to each class are separated away, several disconnected neighborhood graphs will occur, which leads to the failure of ISOMAP. Moreover, ISOMAP behaves in an unsupervised manner and… 

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