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Cited by 82Imbalanced Data Classification TechniquesNeural Networks and ApplicationsMachine Learning and Data Classification

The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.

Neural Learning from Unbalanced Data

Murphey, Yi L., Guo, Hong, Feldkamp, Lee A.·2004·Applied Intelligence
DOI 10.1023/b:apin.0000033632.42843.17
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Crossref · 10.1023/b:apin.0000033632.42843.17

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20 of 20 references verified0 citation errors · 0 not checkable

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  • ANNs and algorithms of the decision tree class, including random forests, can well classify and predict asymmetric data or imbalanced data showing a strong generalization ability.

    “Fortunately, ANNs and algorithms of the decision tree class, including random forests, can well classify and predict asymmetric data or imbalanced data showing a strong generalization ability [110,111,112].”

    From Machine Learning Based Toxicity Prediction: From Chemical Structural Description to Transcriptome Analysis (2018) · cites this paper as [111]

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Metadata

Authors
Murphey, Y. L., Guo, H., & Feldkamp, L. A.
Affiliations
  • University of Michigan–Dearborn (US)
  • Ford Motor Company (United States) (US)
Corresponding author
Murphey, Yi L.
ORCID
Venue
Applied Intelligence
Publisher
Springer Science and Business Media LLC
Published
2004-09
Volume
21
Issue
2
Pages
117-128
ISSN
  • 0924-669X (ISSN-L)
  • 1573-7497
DOI
10.1023/b:apin.0000033632.42843.17
OpenAlex
W2013262041
Cited by
82
References
20
Citations by year
2026: 1 · 2025: 4 · 2024: 5 · 2023: 4 · 2022: 7 · 2021: 4 · 2020: 8 · 2019: 2 · 2018: 4 · 2017: 5 · 2016: 6 · 2015: 3 · 2014: 3 · 2013: 4 · 2012: 1
FWCI
3.38
Type
journal article
Language
en
Open access
closed
Licence
Locations
Applied Intelligence (publishedVersion)
Funders
  • National Science Foundation
  • Ford Motor Company
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Imbalanced Data Classification Techniques
  • Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
  • Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Data Classification
Keywords
class imbalance, noisy data, neural network classification, minority class, oversampling, snowball technique, generalization, BP neural network, radial basis function neural network, fuzzy ARTMAP, noise level measurement, vehicle classification, automotive assembly plant

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