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Efficient Knowledge Discovery for an Intelligent Dataminer
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Venu madhav1,Rajalakshmi Selvaraj2
*1 University of Johannesburg, South Africa, Email : venumadhav_cse@yahoo.com
2 Botho college, Gaborone, Botswana, Email : rajalakshmi.selvaraj@bothocollege.ac.bw
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Abstract
.In every field, data is the most significant property, When the data concealed in the rare data it is exposed. Processing of non-trivial removal of novel, which actionable and implicit information from the huge data is Datamining which is an investigation of data, difficult to find out the most helpful patterns and information, which are not understandable to the data user. It computes the patterns and relationships in a rare data and distributes the outcome which can be either assessed by a human analyst or make use of in automatic decision support system. Multiple stages are available in the Data mining. In data mining very simple process are involved, they are post processing the mined result, pre-processing the data and choosing the suitable mining algorithm. At every stage, these are more option that is probable. With this data mining process, the proposed system is operated by selecting the suitable Data mining algorithm for the user’s needs. Proposed system first performs the pre-processing the data, which converts the data into most appropriate form for use by selecting the algorithm. Pre-processed mined data is post-processed and acquire a pattern as command through the user. The main aim of this project is solved by deploying the developed pattern. This proposed system general structure. This general structure is used for any type of data set and can used as make possible human analysis is the one of the particular tool. This tool mostly used to create intelligence huge quantity of data, which need processing to create knowledgeable conclusion. The conclusion is created by the back propagation method in neural network. At last, propose system the performance and evolution is shown, which clearly explains the proposed system have best tool to choose the appropriate algorithm in data mining.
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Keywords
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Data mining; A-priori algorithm; Pincer search alg; Pattern Recognition; Pincer search algorithm
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URL: http://dx.doi.org/10.7321/jscse.v3.n3.34
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