Analysis of Data Mining Classification with Decision tree Technique

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Provided by: Global Journals
Topic: Data Management
Format: PDF
The diversity and applicability of data mining are increasing day-to-day so need to extract hidden patterns from massive data. The paper states the problem of attribute bias. Decision tree technique based on information of attribute is biased toward multi value attributes which have more but insignificant information content. Attributes that have additional values can be less important for various applications of decision tree. Problem affects the accuracy of ID3 Classifier and generate unclassified region. The performance of ID3 classification and cascaded model of RBF network for ID3 classification is presented here.
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