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Title: A Survey on Data mining classification approaches
Authors: Mishra, A.
Gupta, B. B.
Peraković, D.
García-Peñalvo, F. J.
Keywords: Bagging
Naive Bayes
Random Forest
Data mining
Issue Date: 26-Dec-2021
Citation: Mishra, A., Gupta, B. B., Peraković, D., & García-Peñalvo, F. J. (2021). A Survey on Data mining classification approaches. In Z. Zhou, K. T. Chui, B. B. Gupta, A. M. T, & J. Zhang (Eds.), SysCom 2021. Smart Systems and Advanced Computing 2021. Proceedings of International Conference on Smart Systems and Advanced Computing, New Delhi, India (Virtual Mode), December 26-27, 2021.
Abstract: In this review article, we discuss a number of different classification algorithms used in data mining for unique applications. There are various techniques to analyse the data for continuous and discrete values. Though,in our research paper, we discuss algorithm used for classification and applied for data mining. Basically classification is a technique for categorising data into discrete categories depending on limitations. The Genetic algorithm C4.5, the Naive Bayes algorithm, and others are examples of classification algorithms.
ISSN: 1613-0073
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