K-means clustering with manifold

@article{Wei2010KmeansCW,
  title={K-means clustering with manifold},
  author={Lai Wei and Weiming Zeng and Hong Wang},
  journal={2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery},
  year={2010},
  volume={5},
  pages={2095-2099}
}
K-means clustering is a popular conventional clustering algorithm. As it does not use the structure information of data sets, sometime the clustering result will be dissatisfied. Manifold learning algorithms can reveal the low-dimensional geometry structure of the data sets. In this paper, we combine K-means clustering algorithm with manifold learning algorithms into a coherent framework. We show the proposed algorithms KCM(K-means clustering with manifold) approaches can obtain good clustering… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-7 OF 7 CITATIONS

Advances in Swarm Intelligence

  • Lecture Notes in Computer Science
  • 2012
VIEW 10 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Pattern Analysis of Machine Olfactory System

VIEW 4 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Estimation of Clusters Number and Initial Centers of K-Means Algorithm Using Watershed Method

  • 2015 14th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)
  • 2015
VIEW 1 EXCERPT
CITES METHODS

Opinion mining for thai restaurant reviews using K-Means clustering and MRF feature selection

  • 2015 7th International Conference on Knowledge and Smart Technology (KST)
  • 2015
VIEW 2 EXCERPTS
CITES METHODS & BACKGROUND