UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 4
April-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRBF06072


Registration ID:
194753

Page Number

364-370

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Title

Performance Evaluation of Ensemble Classifiers on Benchmark Datasets

Abstract

In supervised machine learning, highest possible performance is achievable and identifying such a perfect model is a crucial research task. Although a single machine learning algorithm performs well in predicting the target variable, it is not up to the highest possible accuracy that is achievable when used with diverse real data. Hence, the native solution is to come up with ideas to combine the models namely ensemble methods that use multiple supervised machine learning algorithms in order to obtain highest predictive performance than those obtained from any of the contributing algorithms alone. These ensemble methods conceal the disadvantage of those single models and improve the performance to provide the best prediction possible. When the validation process is undertaken, it will describe the quality and characteristics of the ensemble models and predict their performance against real data. In this research work, the performance of the two ensemble classifiers namely Bagging and AdaBoost is experimented and evaluated on various folds of cross validation with different experiments on two different benchmark datasets namely credits and diabetes. The results provide better understanding of the accuracy, reliability and usefulness of the models.

Key Words

Data Mining, Classification, Prediction, Diabetes Classification, Credits Classification, Ensemble Classifier

Cite This Article

"Performance Evaluation of Ensemble Classifiers on Benchmark Datasets", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.364-370, April-2019, Available :http://www.jetir.org/papers/JETIRBF06072.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Performance Evaluation of Ensemble Classifiers on Benchmark Datasets", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp364-370, April-2019, Available at : http://www.jetir.org/papers/JETIRBF06072.pdf

Publication Details

Published Paper ID: JETIRBF06072
Registration ID: 194753
Published In: Volume 6 | Issue 4 | Year April-2019
DOI (Digital Object Identifier):
Page No: 364-370
Country: INDIA, INDIA, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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