Improved Fuzzy FCM-LI Algorithm

Li Bo Hou

doi:10.4028/www.scientific.net/AMR.765-767.670

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 765-767Improved Fuzzy FCM-LI Algorithm

Improved Fuzzy FCM-LI Algorithm

Abstract:

Fuzzy C-means (FCM) clustering algorithm is one of the widely applied algorithms in non-supervision of pattern recognition. However, FCM algorithm in the iterative process requires a lot of calculations, especially when feature vectors has high-dimensional, Use clustering algorithm to sub-heap, not only inefficient, but also may lead to "the curse of dimensionality." For the problem, This paper analyzes the fuzzy C-means clustering algorithm in high dimensional feature of the process, the problem of cluster center is an np-hard problem, In order to improve the effectiveness and Real-time of fuzzy C-means clustering algorithm in high dimensional feature analysis, Combination of landmark isometric (L-ISOMAP) algorithm, Proposed improved algorithm FCM-LI. Preliminary analysis of the samples, Use clustering results and the correlation of sample data, using landmark isometric (L-ISOMAP) algorithm to reduce the dimension, further analysis on the basis, obtained the final results. Finally, experimental results show that the effectiveness and Real-time of FCM-LI algorithm in high dimensional feature analysis.

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Periodical:

Advanced Materials Research (Volumes 765-767)

Pages:

670-673

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.765-767.670

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Online since:

September 2013

Authors:

Li Bo Hou

Keywords:

Fuzzy C-Means Clustering, Insert, Isometric Feature Mapping, Nonlinear Dimensionality Reduction, Styling

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