• Title/Summary/Keyword: OCAEFCM

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Clustering of Incomplete Data Using Autoencoder and fuzzy c-Means Algorithm (AutoEncoder와 FCM을 이용한 불완전한 데이터의 군집화)

  • 박동철;장병근
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.5C
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    • pp.700-705
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    • 2004
  • Clustering of incomplete data using the Autoencoder and the Fuzzy c-Means(PCM) is proposed in this paper. The Proposed algorithm, called Optimal Completion Autoencoder Fuzzy c-Means(OCAEFCM), utilizes the Autoencoder Neural Network (AENN) and the Gradiant-based FCM (GBFCM) for optimal completion of missing data and clustering of the reconstructed data. The proposed OCAEFCM is applied to the IRIS data and a data set from a financial institution to evaluate the performance. When compared with the existing Optimal Completion Strategy FCM (OCSFCM), the OCAEFCM shows 18%-20% improvement of performance over OCSFCM.