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A Survey in Data Mining Prospective for handling Uncertainty and Vagueness

Monika Dandotiya1 , Mahesh Parmar2

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-4 , Page no. 56-61, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i4.5661

Online published on Apr 30, 2019

Copyright © Monika Dandotiya, Mahesh Parmar . 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: Monika Dandotiya, Mahesh Parmar, “A Survey in Data Mining Prospective for handling Uncertainty and Vagueness,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.56-61, 2019.

MLA Style Citation: Monika Dandotiya, Mahesh Parmar "A Survey in Data Mining Prospective for handling Uncertainty and Vagueness." International Journal of Computer Sciences and Engineering 7.4 (2019): 56-61.

APA Style Citation: Monika Dandotiya, Mahesh Parmar, (2019). A Survey in Data Mining Prospective for handling Uncertainty and Vagueness. International Journal of Computer Sciences and Engineering, 7(4), 56-61.

BibTex Style Citation:
@article{Dandotiya_2019,
author = {Monika Dandotiya, Mahesh Parmar},
title = {A Survey in Data Mining Prospective for handling Uncertainty and Vagueness},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {7},
Issue = {4},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {56-61},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3995},
doi = {https://doi.org/10.26438/ijcse/v7i4.5661}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i4.5661}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3995
TI - A Survey in Data Mining Prospective for handling Uncertainty and Vagueness
T2 - International Journal of Computer Sciences and Engineering
AU - Monika Dandotiya, Mahesh Parmar
PY - 2019
DA - 2019/04/30
PB - IJCSE, Indore, INDIA
SP - 56-61
IS - 4
VL - 7
SN - 2347-2693
ER -

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Abstract

Statistical analysis is used in traditional data mining techniques. But this analysis is less prone to real world scenario. The latest innovations in technology databases contain imprecise & vague data. In the field of data mining, handling such data is always a tedious task. During important decision making task the use of imprecise data causes the inconsistency & vagueness. In this paper to handle uncertain data in data mining various mathematical models like fuzzy set, soft set, rough set & vague set are projected. Various productive approaches have already renewed the Association rule mining. Comparative study of various models defines the idea for using particular set theory. To deal with commercial management & business decision making problem, for generating profitable patterns here we are trying to explore the concept of different set theory. These are also the main benefits of this paper.

Key-Words / Index Term

Data mining, Vagueness, uncertainty, fuzzy set, vague set, Gray set, rough set & association rule mining

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