Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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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. The performance of hybrid technique ID3 with CRBF for classification is proposed. As shown through the experimental results ID3 classifier with CRBF accuracy is higher than ID3 classifier.
Jully Samota. 2014. \u201cAnalysis of Data Mining Classification with Decision Tree Technique\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 13 (GJCST Volume 13 Issue C13): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
Total Score: 103
Country: India
Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering
Authors: Dharm Singh, Naveen Choudhary, Jully Samota (PhD/Dr. count: 0)
View Count (all-time): 229
Total Views (Real + Logic): 9062
Total Downloads (simulated): 2348
Publish Date: 2014 01, Sun
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Neural Networks and Rules-based Systems used to Find Rational and
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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. The performance of hybrid technique ID3 with CRBF for classification is proposed. As shown through the experimental results ID3 classifier with CRBF accuracy is higher than ID3 classifier.
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