關聯推理神經網路

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Title:	關聯推理神經網路
Authors:	葉怡成 Yeh, I-Cheng
Contributors:	資訊管理學系 Information Management
Keywords:	資料探勘;類神經網路;關聯規則;關聯分析 Artificial;network;association;rule;data mining
Date:	2008
Issue Date:	2014-06-27 01:40:48 (UTC+8)
Abstract:	本研究所提出的關聯推理神經網路(Association Reasoning Neural Networks, ARNN)是修改自倒傳遞神經網路演算法，可以產生關聯規則，為傳統的關聯分析開啟完全不同的研究途徑。經由一個數值例題與一個實際例題的結果歸納出以下結論：(1) ARNN的推論輸出值與資料中的信賴度大約相等。(2) 當ARNN的隱藏單元數減少時，檢出率、準確率會跟著變小。(3)ARNN可以利用減少隱藏單元數來避免產生信賴度過低的關聯規則。(4)ARNN產生的規則與由傳統關聯分析法所找到的規則重疊性很高 In this study, we proposed the Association Reasoning Neural Network (ARNN) which is derived from ANN, can produce association rules, and open a new approach for association analysis. Based on a numerical and a practical example, some conclusions can be go
Appears in Collections:	[Department of Information Management] Journal Articles

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