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Comparative Analysis of Data Mining Techniques

Shaganpreet Kaur1 , Chinu 2

  1. C.S.E, Baba Farid College of Engineering and Technology, Bathinda, Punjab.
  2. C.S.E, Baba Farid College of Engineering and Technology, Bathinda, Punjab.

Section:Review Paper, Product Type: Journal Paper
Volume-6 , Issue-4 , Page no. 301-304, Apr-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i4.301304

Online published on Apr 30, 2018

Copyright © Shaganpreet Kaur, Chinu . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Shaganpreet Kaur, Chinu, “Comparative Analysis of Data Mining Techniques,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.301-304, 2018.

MLA Style Citation: Shaganpreet Kaur, Chinu "Comparative Analysis of Data Mining Techniques." International Journal of Computer Sciences and Engineering 6.4 (2018): 301-304.

APA Style Citation: Shaganpreet Kaur, Chinu, (2018). Comparative Analysis of Data Mining Techniques. International Journal of Computer Sciences and Engineering, 6(4), 301-304.

BibTex Style Citation:
@article{Kaur_2018,
author = {Shaganpreet Kaur, Chinu},
title = {Comparative Analysis of Data Mining Techniques},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2018},
volume = {6},
Issue = {4},
month = {4},
year = {2018},
issn = {2347-2693},
pages = {301-304},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1888},
doi = {https://doi.org/10.26438/ijcse/v6i4.301304}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i4.301304}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1888
TI - Comparative Analysis of Data Mining Techniques
T2 - International Journal of Computer Sciences and Engineering
AU - Shaganpreet Kaur, Chinu
PY - 2018
DA - 2018/04/30
PB - IJCSE, Indore, INDIA
SP - 301-304
IS - 4
VL - 6
SN - 2347-2693
ER -

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Abstract

Data mining is the area of research, which means that useful information or knowledge is extracted from previous data. Data mining defines large amounts of data as a process of finding information such as super market data for various technologies used for data mining, such as science, research, medicine, media, web, entertainment and many other areas, which is implemented with various goods, data mining model data warehouses and online analytical resources. Data mining has made a immense advancement in recent year but the problem of lost data has remained a big challenge for data mining algorithms. This paper analyzed the predictive and descriptive techniques such as classification, regression time series analysis ,predication and clustering, summarization, association rules, sequence discovery techniques on the basis of algorithms which is used to predict previously unidentified class of objects.

Key-Words / Index Term

Data mining, Data mining techniques: Predictive and Descriptive DM techniques

References

[1]. Deepashri.K.S Asst. Professor, Dept. of IS&E Adichunchangiri Institute of Technology, Chikmaglur, Karnataka, India ‘Survey on Techniques of Data Mining and its Applications’, International Journal of Emerging Research in Management &Technology , ISSN: 2278-9359 (Volume-6, Issue-2).
[2]. Radhakrishnan Gopalapillaia* , Deepa Guptab, Sudarshan TSBa, ‘Pattern Identification of Robotic Environments using Machine Learning Techniques’, 7th International Conference on Advances in Computing & Communications, ICACC-2017, 22-24 August 2017, Cochin, India.
[3]. Eunseog Youn a, Myong K. Jeong b,’Class dependent feature scaling method using naive Bayes classifier for text datamining’, Article history: Received 18 September 2007 Received in revised for 1August 2008 Available online 24 December 2008.
[4].Mansi Gera, Shivani Goel," Data Mining-Techniques,Methods and Algorithms:A Review on Tools and their Validity", International Journal of Computer Applications (0975 –8887)Volume 113–No. 18, March 2015.
[5]. Ayman E. Khedra, Mona Kadryb, Ghada Walidb, ’Proposed framework for implementing data mining techniques to enhance decisions in agriculture sector Applied case on Food Security Information Center Ministry of Agriculture’, Egypt International Conference on Communication, Management and Information Technology (ICCMIT 2015).
[6]. Vikas Gupta, Prof. Devanand ‘A survey on Data Mining: Tools, Techniques, Applications, Trends and Issues’, International Journal of Scientific & Engineering Research Volume 4, Issue3, March-2013 1ISSN2229-5518.
[7].Kochetov Vadim National Research Nuclear University MEPhI(Moscow Engineering Physics Institute),Moscow, Russian Federation Ko4etovvadim@gmail.com,"Overview of different approaches to solving problems of Data Mining", Procedia Computer Science 123 (2018)234–239.
[8].Ruili Wang etl.,"Review on mining data from multiple data sources", January 27, 2018.