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Volume & Issue no: Volume 3, Issue 6, November - December 2014

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Title:
Performance Evaluation of Decision Trees for Uncertain Data Mining
Author Name:
Ms. Kiran Dhandore, Dr. Lata Ragha
Abstract:
Abstract Decision trees are considered to be one of the most popular approaches for representing classifiers. Researchers from various disciplines such as statistics, machine learning, pattern recognisition and Data Mining have dealt with the issue of growing a decision tree from available data. Traditional decision tree classifiers used to work on the data whose values are known and precise. Therefore in this research such classifiers are used to handle data with uncertain information. Two approaches has been implemented one is the averaging in which the data uncertainty is represented by abstract probability distribution by summary statistics such as mean and variances. The other approach is the distribution based which considers all the sample points that constitute each pdf. Keywords:- Decision Trees, Uncertain data, Pruning, Entropy, Classification.
Cite this article:
Ms. Kiran Dhandore, Dr. Lata Ragha , " Performance Evaluation of Decision Trees for Uncertain Data Mining" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 3, Issue 6, November - December 2014 , pp. 107-111 , ISSN 2278-6856.
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
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