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Comparative Study and Analysis of Audit Data Using Data Mining Tools

R. Deepa Lakshmi, N. Radha

Abstract


Data mining process discovers useful information from the hidden data, which can be used for future prediction. Machine learning provides methods, techniques and tools, which help to learn automatically and to make accurate predictions based on past observations. This paper presents an implementation of various data mining tools in real time datasets. The main purpose of this paper is to provide a comparison of some commonly employed classification algorithms under the same conditions. Such comparison helps to provide the accurate result in algorithms. Hence comparing the algorithms for such a classifier is a tedious task, for real time dataset. The classification models were experimented by using 365 datasets. The predicted values for the classifiers were evaluated and the results were compared.

Keywords


Audit Selection Strategy, Machine-Learning Techniques, Open Source Tools, Data Mining, Naive Bayes, Tax Audit

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References


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