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Article citations


H. Hotelling, “Analysis of a Complex of Statistical Variables into Principal Components,” Journal of Educational Psychology, Vol. 24, 1933, 417-441. doi:10.1037/h0071325

has been cited by the following article:

  • TITLE: Supervised Fuzzy Mixture of Local Feature Models

    AUTHORS: Mingyang Xu, Michael Golay

    KEYWORDS: Adaptive Fuzzy Mixture, Supervised Clustering, Local Feature Model, PCA, ICA, Phase Transition, Fuzzy Parametric Clustering, Real-Coded Genetic Algorithm

    JOURNAL NAME: Intelligent Information Management, Vol.3 No.3, April 29, 2011

    ABSTRACT: This paper addresses an important issue in model combination, that is, model locality. Since usually a global linear model is unable to reflect nonlinearity and to characterize local features, especially in a complex sys-tem, we propose a mixture of local feature models to overcome these weaknesses. The basic idea is to split the entire input space into operating domains, and a recently developed feature-based model combination method is applied to build local models for each region. To realize this idea, three steps are required, which include clustering, local modeling and model combination, governed by a single objective function. An adaptive fuzzy parametric clustering algorithm is proposed to divide the whole input space into operating regimes, local feature models are created in each individual region by applying a recently developed fea-ture-based model combination method, and finally they are combined into a single mixture model. Corre-spondingly, a three-stage procedure is designed to optimize the complete objective function, which is actu-ally a hybrid Genetic Algorithm (GA). Our simulation results show that the adaptive fuzzy mixture of local feature models turns out to be superior to global models.