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Research and Implementation of Visual Data Mining

Author: YuYang
Tutor: LiZhanShan
School: Jilin University
Course: Computer Software Engineering
Keywords: Data Mining Data Mining Visualization Star coordinates Clustering
CLC: TP311.52
Type: Master's thesis
Year: 2008
Downloads: 283
Quote: 3
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Visual data mining is an important data mining method , which uses data visualization technology as a channel of communication between the computer and the user information , abstract information is presented in a concise graphical form , and to discover novel mode and easily understood . Visual data mining techniques can be more intuitive and easily from the large amount of data to find useful rules and information , its purpose is to make better use of the model for visual form and structure of the ability to obtain , and then guide the excavation work , understanding mining results . In this paper, a visual data mining are three main ways : data visualization , mining process visualization and results visualization . Visualization module prototype data mining system , visual data mining functions with good ease of use and scalability . Users can easily through data visualization observed data distribution and statistical information , effective control of the data mining process , combined with an intuitive graphic display of mining results , to see and understand the mining results . The article also focuses on the application of the star coordinates visualization technology clustering algorithm . Star coordinate method to achieve a large - scale data and the larger dimension of the visualization of the data set . Traditional density - based clustering algorithm DBSCAN the neighborhood parameters Eps select sensitive shortcomings through the the star axis of rotation , scaling , image scaling , the data point of view , selection and coloring operations to observe and record test data set , and constantly improve the parameters of the algorithm to help users understand the results of data mining algorithms until the completion of the interactive data mining .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Software Engineering > Software Development
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