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  Published Paper Details:

  Paper Title

OPTIMIZING IMBALANCED DATA CLASSIFICATION THE OWA-ELM APPROACH

  Authors

  ,K.Triveni,  Mr.N.Sravankumar

  Keywords

Imbalanced Data, OWA-ELM

  Abstract


In the realm of machine learning, the Extreme Learning Machine (ELM) excels in classification and regression but falters with imbalanced data. To address this, we introduce OWA-ELM, an enhanced ELM algorithm with output weight adjustment. OWA-ELM strategically adjusts connection weights to favor minority classes, improving their classification accuracy without compromising majority class performance. Furthermore, we integrate OWA-ELM with the deep learning SMOTE algorithm to automatically synthesize similar data, addressing data imbalance more effectively. Our extended OWA-ELM with SMOTE outperforms other algorithms, achieving higher FSCOREs and demonstrating superior classification performance on imbalanced datasets.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2405135

  Paper ID - 259119

  Page Number(s) - b246-b257

  Pubished in - Volume 12 | Issue 5 | May 2024

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  ,K.Triveni,  Mr.N.Sravankumar,   "OPTIMIZING IMBALANCED DATA CLASSIFICATION THE OWA-ELM APPROACH", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 5, pp.b246-b257, May 2024, Available at :http://www.ijcrt.org/papers/IJCRT2405135.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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