Manuscript Number : SHISRRJ18137

A Study of Machine Learning Techniques in Data Mining

Authors(2) :-Nithya C, Saravanan V

Data mining is the process of discovering interesting knowledge patterns from large amount of data stored in database. It is an essential process where the intelligent techniques (i.e., machine learning, artificial intelligence, etc ) are used to extract the data patterns (i.e., features). The aim of data mining process is to extract the useful information from dataset and transform it into understandable structure for future use. Machine learning is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed. In machine learning, feature learning or representation learning is a set of techniques that allows a system to automatically discover the representations needed for feature detection or classification from raw data.

Authors and Affiliations

Nithya C
Department of Computer Science, Hindusthan College of Arts And Science, Coimbatore, India
Saravanan V
Department of Computer Science, Hindusthan College of Arts And Science, Coimbatore, India

Data Mining, Machine learning, Feature Learning.

  1. https://www.mathworks.com/discovery/machine-learning.html
  2. https://www.import.io/post/data-mining-machine-learning-difference/
  3. https://neilpatel.com/blog/data-mining/
  4. https://importoioweb.staging.wpengine.com/solutions/machine-learning/
  5. https://en.wikipedia.org/wiki/Machine_learning
  6. Coates, Adam; Lee, Honglak; Ng, Andrew Y. (2011). An analysis of single-layer networks in unsupervised feature learning (PDF). Int'l Conf. on AI and Statistics (AISTATS).
  7. Csurka, Gabriella; Dance, Christopher C.; Fan, Lixin; Willamowski, Jutta; Bray, Cédric (2004). Visual categorization with bags of keypoints (PDF). ECCV Workshop on Statistical Learning in Computer Vision.
  8. Daniel Jurafsky; James H. Martin (2009). Speech and Language Processing. Pearson Education International. pp. 145–146.
  9. Bengio; A. Courville; P. Vincent (2013). "Representation Learning: A Review and New Perspectives". IEEE Trans. PAMI, special issue Learning Deep Architectures. 35: 1798–1828. arXiv:1206.5538  . doi:10.1109/tpami.2013.50.
  10. Fayyad, Usama; Piatetsky-Shapiro, Gregory; Smyth, Padhraic (1996). "From Data Mining to Knowledge Discovery in Databases" (PDF). Retrieved 17 December 2008.

Publication Details

Published in : Volume 1 | Issue 3 | September-October 2018
Date of Publication : 2018-10-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 31-34
Manuscript Number : SHISRRJ18137
Publisher : Shauryam Research Institute

ISSN : 2581-6306

Cite This Article :

Nithya C, Saravanan V, "A Study of Machine Learning Techniques in Data Mining", Shodhshauryam, International Scientific Refereed Research Journal (SHISRRJ), ISSN : 2581-6306, Volume 1, Issue 3, pp.31-34, September-October.2018
URL : https://shisrrj.com/SHISRRJ18137

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