Volume : IV, Issue : IX, September - 2014
Comparison of Association Rules, Clustering and Decision Tree Data Mining Models‘ Accuracy: A Case Study of Birth Registration E–governance data
Pushpal Desai
Abstract :
The Data Mining algorithms are widely used for knowledge discovery. The researchers are using different Data Mining algorithms like Association Algorithm, Clustering Algorithm, Decision Trees Algorithm, Linear Regression Algorithm, Logistic Regression Algorithm, Naive Bayes Algorithm, Neural Network Algorithm, Time Series Algorithm etc…for knowledge discovery. Many times different algorithms are applied for solving the same problem and in that scenario, it is important to indentify which algorithm will be the most effective. In this paper, the mining model accuracy is applied to understand quality and accuracy for different data mining models. The lift chart is created considering Association Rules, Clustering and Decision Trees data mining models. The results indicate that lift chart is very effective for evaluating accuracy of different data mining models.
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DOI : 10.36106/ijar
Cite This Article:
Pushpal Desai Comparison of Association Rules, Clustering and
Decision Tree Data Mining Models¥ Accuracy: A Case Study of Birth Registration E-governance data Indian Journal of Applied Research, Vol.4, Issue.9 September 2014
Number of Downloads : 712
Pushpal Desai Comparison of Association Rules, Clustering and Decision Tree Data Mining Models¥ Accuracy: A Case Study of Birth Registration E-governance data Indian Journal of Applied Research, Vol.4, Issue.9 September 2014
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