Who Cited It

Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning

2005 · Lecture notes in computer science · 4,049 citations · 7 from inside this corpus

Hui Han, Wenyuan Wang, Binghuan Mao low

No abstract in the source record.

Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning (2005)Borderline-SMOTE: A New Over-…SMOTE: Synthetic Minority Over-sampling Technique (2002)SMOTE: Synthetic Minority Ove…C4.5: Programs for Machine Learning (1992)C4.5: Programs for Machine Le…UCI Repository of machine learning databases (1998)UCI Repository of machine lea…The use of the area under the ROC curve in the evaluation of machine learning algorithms (1997)The use of the area under the…A study of the behavior of several methods for balancing machine learning training data (2004)A study of the behavior of se…Editorial (2004)EditorialSMOTEBoost: Improving Prediction of the Minority Class in Boosting (2003)SMOTEBoost: Improving Predict…Mining with rarity (2004)Mining with rarityLearning from Imbalanced Data (2009)Learning from Imbalanced DataA systematic study of the class imbalance problem in convolutional neural networks (2018)A systematic study of the cla…Survey on deep learning with class imbalance (2019)Survey on deep learning with …SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Ann… (2018)SMOTE for Learning from Imbal…RUSBoost: A Hybrid Approach to Alleviating Class Imbalance (2009)RUSBoost: A Hybrid Approach t…An insight into classification with imbalanced data: Empirical results and current trends… (2013)An insight into classificatio…Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine … (2016)Imbalanced-learn: A Python To…
15 of 15 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
this paper works it cites works citing it node size = global citations · hover for the full title

What this paper cites, inside the corpus

PaperYearCited
SMOTE: Synthetic Minority Over-sampling Technique200232,402
C4.5: Programs for Machine Learning199223,704
UCI Repository of machine learning databases199810,546
The use of the area under the ROC curve in the evaluation of machine learning algorithms19977,328
A study of the behavior of several methods for balancing machine learning training data20044,222
Editorial20042,081
SMOTEBoost: Improving Prediction of the Minority Class in Boosting20031,680
Mining with rarity20041,396

What cites it, inside the corpus

PaperYearCited
Learning from Imbalanced Data200910,209
A systematic study of the class imbalance problem in convolutional neural networks20183,072
Survey on deep learning with class imbalance20192,971
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Ann…20182,226
RUSBoost: A Hybrid Approach to Alleviating Class Imbalance20091,890
An insight into classification with imbalanced data: Empirical results and current trends…20131,602
Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine …20161,561

Links

DOI · OpenAlex record

Topics

Imbalanced Data Classification TechniquesComputer Science
Text and Document Classification TechnologiesComputer Science
Rough Sets and Fuzzy LogicComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports3 author record(s) attached.
  • supports29 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:46+00:00.

sha256 bba2969b3567609a…