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    題名: 應用Bayesian架構發展分類學習模型
    其他題名: Categorization by local relationship among exemplars
    作者: 楊立行;許清芳;鄭惟尹;蔡涵如
    Yang,Lee-Xieng
    貢獻者: 國立政治大學心智、大腦與學習研究中心
    日期: 2009
    上傳時間: 2013-10-09 17:27:31 (UTC+8)
    摘要: The principal purpose of this study is to develop a categorization model with Bayesian
    theorems. The developed model SOE holds the assumptions that the percept of each
    input is represented as a normal distribution over the units on the stimulus dimension and
    that the classi cation is made by referencing the weighted strengths over the units within
    the scope of attention focus. SOE in this study is evident to be sensitive to the repetition
    of stimuli, stimulus order, and, the most important, the variability e ect in categorization.
    This e ect is thought to be a severe challenge to the exemplar-based models. However, the
    success of SOE suggests a possible exemplar-based account for this e ect.
    關聯: 執行期間：9708-9809
    資料類型: report
    顯示於類別:[心智‧大腦與學習研究中心 ] 國科會研究計畫

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    96-2413-H-004-020-MY2.pdf325KbAdobe PDF2662檢視/開啟


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