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Technology Research, Data Mining Based On Fuzzy Clustering

Posted on:2003-03-28Degree:MasterType:Thesis
Country:ChinaCandidate:S G GaoFull Text:PDF
GTID:2208360065461417Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
Data mining is a relatively young research and application area based on Database techniques, which synthesizes multidisciplinary productions, such as logic, statistics, machine learning, fuzzy theory and visual computing, in order to acquire usable information from database. It has achieved increasing attention and broadly interest in the past years.The paper includes the author's research work on three aspects. Firstly, the author analyzes principles and general methods of clustering-based Data Mining; secondly, summarizes the definition of clustering and Data Mining, the correlative techniques and present research status inland as well as overseas; lastly, makes improvement on fuzzy C-average clustering algorithm and studies on soft clustering algorithm.Fuzzy C- average clustering algorithm is one of the earliest goal-function clustering algorithms, which has achieved much attention. However, it remains several weaknesses and insufficiency. The signification of subjection value is one of the weaknesses. Aiming at the insufficient situation, the paper presents further research work on subjection value, which explains the concept from the point of view of compete learning. Soft clustering algorithm can improve the speed of fuzzy C- average clustering algorithm. The paper presents a new soft clustering algorithm based on the new signification of subjection value. The analysis on theory and experiments show that the new algorithm can improve the convergence speed of fuzzy C- average clustering algorithm.
Keywords/Search Tags:Data Mining, Clustering Analysis, Fuzzy Clustering, Clustering Effectivity, Fuzzy C- average Clustering Algorithm
PDF Full Text Request
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