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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM25105
Volume:
7 |
8 |
Aug 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
[ Data mining technology, driven by machine learning algorithms, has emerged as a powerful approach for extracting valuable insights and patterns from large-scale datasets. This research paper provides an in-depth analysis of the advancements, challenges, and future directions in data mining technology based on machine learning algorithms. The paper explores key areas such as classification, clustering, association rule, mining, anomaly detection, feature selection, deep learning, privacy preservation, stream mining, transfer learning, and explainability. It discusses the significance of each area, highlights notable research contributions, and presents the challenges faced by researchers. Moreover, the paper outlines potential solutions to address these challenges and proposes future directions for advancing the field. By providing a comprehensive overview, this research paper aims to contribute to the understanding of data mining technology and its application in various domains.
KEYWORDS
Publication Date
7/7/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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