AN EMPIRICAL STUDY OF DIFFERENT DATA MINING TECHNIQUES AND ALGORITHMS

Authors

  • Jismy Joseph PhD Research Scholar Department of Computer Science, Vivekanandha College of Arts and Science for Women (Autonomous), Elayampalayam, Thiruchengode, Tamil N
  • Dr.G. Kesavaraj Professor and head Department of Computer Science, Vivekanandha College of Arts and Science for Women (Autonomous), Elayampalayam, Thiruchengode, Tamil Nadu, Indi

Keywords:

Data mining Techniques, Classification, prediction, Clustering, k-NN, Naïve Bayes classifier, Decision Tree, C4.5, classification

Abstract

Data mining is a process to find hidden information from a large data set. Data mining technologies are used nowadays in various sectors like banking, healthcare, education, marketing etc. One of the most important challenges in data mining is to choose the correct data mining technique and algorithm based on the type of problems tackled by businesses. A generalized approach can improve the accuracy and cost effectiveness of data mining process. The aim of this article is to give a comprehensive review of the most frequently considered techniques and algorithms for data mining

Downloads

Published

2018-12-19

How to Cite

Joseph, J., & Kesavaraj, . D. (2018). AN EMPIRICAL STUDY OF DIFFERENT DATA MINING TECHNIQUES AND ALGORITHMS. International Journal of Technical Innovation in Modern Engineering & Science, 4(12), 109–113. Retrieved from https://ijtimes.com/index.php/ijtimes/article/view/107

Issue

Vol. 4 No. 12 (2018): Vol. 4 No. 12: Volume 4 Issue 12 (December-2018)

Section

Articles