IEEE Style Citation: V. Krishnaiah, G. Narsimha, N.S. Chandra, “Survey of Classification Techniques in Data Mining,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.9, pp.65-74, 2014.
MLA Style Citation: V. Krishnaiah, G. Narsimha, N.S. Chandra "Survey of Classification Techniques in Data Mining." International Journal of Computer Sciences and Engineering 2.9 (2014): 65-74.
APA Style Citation: V. Krishnaiah, G. Narsimha, N.S. Chandra, (2014). Survey of Classification Techniques in Data Mining. International Journal of Computer Sciences and Engineering, 2(9), 65-74.
BibTex Style Citation:
@article{Krishnaiah_2014,
author = {V. Krishnaiah, G. Narsimha, N.S. Chandra},
title = {Survey of Classification Techniques in Data Mining},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2014},
volume = {2},
Issue = {9},
month = {9},
year = {2014},
issn = {2347-2693},
pages = {65-74},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=256},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=256
TI - Survey of Classification Techniques in Data Mining
T2 - International Journal of Computer Sciences and Engineering
AU - V. Krishnaiah, G. Narsimha, N.S. Chandra
PY - 2014
DA - 2014/10/04
PB - IJCSE, Indore, INDIA
SP - 65-74
IS - 9
VL - 2
SN - 2347-2693
ER -
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Abstract
Classification in data mining is a technique based on machine learning algorithms which uses mathematics, statistics, probability distributions and artificial intelligence... To predict group membership for data items or to represent descriptive analysis of data items for effective decision making .Now a day�s data mining is touching every aspect of individual life includes Data Mining for Financial Data Analysis, Data Mining for the Telecommunications Industry Data Analysis, Data Mining for the Retail Industry Data Analysis, Data Mining in Healthcare and Biomedical Research Data Analysis, and Data Mining in Science and Engineering Data Analysis, etc. The goal of this survey is to provide a comprehensive review of different classification techniques in data mining based on decision tree, rule based Algorithms, neural networks, support vector machines, Bayesian networks, and Genetic Algorithms and Fuzzy logic.
Key-Words / Index Term
Classifiers, Data Mining Techniques, Intelligent Data Analysis, Learning Algorithms, Artificial Intelligence, Decision Support System, Data Mining, KDD, Classification Algorithms, Fuzzy sets, Genetic Algorithm,etc
References
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