A study of dealing class imbalance problem with machine learning methods for code smell severity detection using PCA-based feature selection technique Article Swipe

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Rajwant Singh Rao , Seema Dewangan , Alok Mishra , Manjari Gupta ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.1038/s41598-023-43380-8

Related Topics

Code Smell

Computer Science

Machine Learning

Artificial Intelligence

Concepts

Code smell Computer science Machine learning Artificial intelligence Random forest Feature selection Decision tree Class (philosophy) Code refactoring Code (set theory) Data mining Software Source code Software quality Software development Programming language Set (abstract data type) Operating system

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Type: article
Language: en
Landing Page: https://doi.org/10.1038/s41598-023-43380-8
PDF: https://www.nature.com/articles/s41598-023-43380-8.pdf
OA Status: gold
Cited By: 31
References: 36
Related Works: 10
OpenAlex ID: https://openalex.org/W4387078716

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DOI: https://doi.org/10.1038/s41598-023-43380-8

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Title: A study of dealing class imbalance problem with machine learning methods for code smell severity detection using PCA-based feature selection technique

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Type: article

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Language: en

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Publication year: 2023

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Publication date: 2023-09-27

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Authors: Rajwant Singh Rao, Seema Dewangan, Alok Mishra, Manjari Gupta

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Landing page: https://doi.org/10.1038/s41598-023-43380-8

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Concepts: Code smell, Computer science, Machine learning, Artificial intelligence, Random forest, Feature selection, Decision tree, Class (philosophy), Code refactoring, Code (set theory), Data mining, Software, Source code, Software quality, Software development, Programming language, Set (abstract data type), Operating system

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Cited by: 31

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Citations by year (recent): 2025: 16, 2024: 13, 2023: 2

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