• NUWAMANYA EZRA MATAGAIZI

ABSTRACT. In a generation revolutionized and anchored by information technology, data is primarily part of the core fundamentals of every innovation and development. This data is undoubtedly in big chunks referred to as big data and as the name suggests, these are extremely huge and complex data sets that may be analyzed computationally to reveal patterns, trends and associations in analytical applications. The assignment of adequate processing and utilization of such large unstructured, semi-structured and structured data sets could no longer be efficiently dealt with by traditional data processing application software and hence the emerging of data mining. Data mining, a practice that critically examines big data for information or knowledge extraction was deployed to substitute the unyielding traditional methods. A result oriented data mining process links to use of well-defined data mining techniques. The most popular data mining techniques include; Association, Clustering, Classification, Decision Tree, Sequential Patterns, Prediction etc. This research seminar paper aims at comparing three (3) of these prominent techniques (Association, Clustering and Classification) in attempt to discover why, how, where and when they are used in data mining!

Keywords: Data mining, Data mining techniques, Association rule, Clustering, Classification.

"DATA MINING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 4, page no.559-562, April-2020, Available :http://www.jetir.org/papers/JETIR2004279.pdf

"DATA MINING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 4, page no. pp559-562, April-2020, Available at : http://www.jetir.org/papers/JETIR2004279.pdf