Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Big Data Mining Algorithms

Big Data Mining Algorithms
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Author(s): M. Govindarajan (Annamalai University, India)
Copyright: 2021
Pages: 10
Source title: Encyclopedia of Information Science and Technology, Fifth Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-7998-3479-3.ch052


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Big data mining involves knowledge discovery from these large data sets. The purpose of this chapter is to provide an analysis of different machine learning algorithms available for performing big data analytics. The machine learning algorithms are categorized in three key categories, namely, supervised, unsupervised, and semi-supervised machine learning algorithm. The supervised learning algorithms are trained with a complete set of data, and thus, the supervised learning algorithms are used to predict/forecast. Example algorithms include logistic regression and the back propagation neural network. The unsupervised learning algorithms starts learning from scratch, and therefore, the unsupervised learning algorithms are used for clustering. Example algorithms include: the Apriori algorithm and K-Means. The semi-supervised learning combines both supervised and unsupervised learning algorithms. The semi-supervised algorithms are trained, and the algorithms also include non-trained learning.

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