Business Intelligence

Performance Analysis of Various Data Mining Algorithms: A Review

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Executive Summary

Data warehouse is the essential point of data combination for business intelligence. Now-a-days, there has been emerging trends in database to discover useful patterns and/or correlations among attributes, called data mining. This paper presents the data mining techniques like classification, clustering and associations analysis which include algorithms of decision tree (like C4.5), rule set classifier, kNN and Na?ve Bayes, clustering algorithms (like k-Means and EM) machine learning (like SVM), association analysis (like Apriori). These algorithms are applied on data warehouse for extracting useful information. All algorithms contain their description, impact and review of algorithm. The authors also show the comparison between the classifiers by accuracy which shows ruleset classifier have higher accuracy when implement in weka.

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