Paper Citation Record · LEDGER

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data

As of 14 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2501.04099.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.04099 v1

Coverage vector

measured 43 of 43 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation 35d7342a-eaca-4b89-9fff-672bc15ed5bd · outbound

This paper cites Thippa Reddy, Celestine Iwendi, Ali Kashif Bashir, and Ohyun Jo.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Thippa Reddy, Celestine Iwendi, Ali Kashif Bashir, and Ohyun Jo

Reference 1

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Observation 67a6eea0-c333-448c-ba61-1f498c478a8e · outbound

This paper cites Random CapsNet forest model for imbalanced malware type classification task.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Random CapsNet forest model for imbalanced malware type classification task

Reference 2

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Observation aff2d8c3-d52a-4aa4-a93e-ce655abd76df · outbound

This paper cites Automated imbalanced classification via meta-learning.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Automated imbalanced classification via meta-learning

Reference 3

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Observation 9d005ec2-169e-4905-915e-da1978e7b0cd · outbound

This paper cites RN-SMOTE: Reduced Noise SMOTE based on DBSCAN for enhancing imbalanced data classification.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data RN-SMOTE: Reduced Noise SMOTE based on DBSCAN for enhancing imbalanced data classification

Reference 4

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Observation 8bc9fada-2381-487d-88ac-b1be5805a701 · outbound

This paper cites Grouping-based Oversampling in Kernel Space for Imbalanced Data Classification.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Grouping-based Oversampling in Kernel Space for Imbalanced Data Classification

Reference 5

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Observation 65115e76-c551-4f45-b640-4ff4fc11984b · outbound

This paper cites Self-adaptive oversampling method based on the complexity of minority data in imbalanced datasets classification.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Self-adaptive oversampling method based on the complexity of minority data in imbalanced datasets classification

Reference 6

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Observation 86ab32dd-18c4-49c6-afd7-8b73e04984b1 · outbound

This paper cites Review of resampling techniques for the treatment of imbalanced industrial data classification in equipment condition monitoring.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Review of resampling techniques for the treatment of imbalanced industrial data classification in equipment condition monitoring

Reference 7

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Observation 0ba86380-f1d6-47f7-94d6-9de04894aab9 · outbound

This paper cites Madkour, Hatem M.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Madkour, Hatem M

Reference 8

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This paper cites What makes multi-class imbalanced problems difficult? An experimental study.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data What makes multi-class imbalanced problems difficult? An experimental study

Reference 9

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Observation c28a5f6e-a04d-4e01-84cf-13979824b0de · outbound

This paper cites Classification of Imbalanced Data Set in Financial Field Based on Combined Algorithm.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Classification of Imbalanced Data Set in Financial Field Based on Combined Algorithm

Reference 10

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Observation 19f7abce-ba61-4a16-be90-c84072f88a2e · outbound

This paper cites Deep transfer network with joint distribution adaptation: A new intelligent fault diagnosis framework for industry application.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Deep transfer network with joint distribution adaptation: A new intelligent fault diagnosis framework for industry application

Reference 11

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Observation 4118a064-6c42-4a37-8502-635d75d4bfd4 · outbound

This paper cites Bajaj, Abhishek D.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Bajaj, Abhishek D

Reference 12

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This paper cites Imbalanced Sample Selection with Deep Reinforcement Learning for Fault Diagnosis.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Imbalanced Sample Selection with Deep Reinforcement Learning for Fault Diagnosis

Reference 13

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Observation f8e30a21-3444-4315-b8fb-cbadd81159a4 · outbound

This paper cites Systematic review of class imbalance problems in manufac- turing.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Systematic review of class imbalance problems in manufac- turing

Reference 14

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Observation 7b913bc7-b692-41ca-98b0-74c6a9781085 · outbound

This paper cites A broad review on class imbalance learning techniques.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data A broad review on class imbalance learning techniques

Reference 15

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This paper cites Boosting methods for multi-class imbalanced data classification: an experimental review.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Boosting methods for multi-class imbalanced data classification: an experimental review

Reference 16

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Observation 30df8e22-56f7-4cbb-b97a-b09a868ebab7 · outbound

This paper cites A modified real-value negative selection detector-based over- sampling approach for multiclass imbalance problems.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data A modified real-value negative selection detector-based over- sampling approach for multiclass imbalance problems

Reference 17

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This paper cites M.Nadim Shahariar, and Muhammed J.A.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data M.Nadim Shahariar, and Muhammed J.A

Reference 18

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This paper cites RGAN-EL: A GAN and ensemble learning-based hybrid approach for imbalanced data classification.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data RGAN-EL: A GAN and ensemble learning-based hybrid approach for imbalanced data classification

Reference 19

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This paper cites Generative adversarial network in mechanical fault diagnosis under small sample: A systematic review on applications and future perspectives.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Generative adversarial network in mechanical fault diagnosis under small sample: A systematic review on applications and future perspectives

Reference 20

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This paper cites Augmentation of Decision Tree Model Through Hyper-Parameters Tuning for Monitoring of Cutting Tool Faults Based on Vibration Signatures.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Augmentation of Decision Tree Model Through Hyper-Parameters Tuning for Monitoring of Cutting Tool Faults Based on Vibration Signatures

Reference 21

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Observation 43167f4a-99fe-4776-bbbd-e329f902fbf2 · outbound

This paper cites Impact of noise model on the performance of algorithms for fault diagnosis in rolling bearings.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Impact of noise model on the performance of algorithms for fault diagnosis in rolling bearings

Reference 22

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This paper cites Iterative minority oversampling and its ensem- ble for ordinal imbalanced datasets.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Iterative minority oversampling and its ensem- ble for ordinal imbalanced datasets

Reference 23

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Observation 8733991e-8c5e-47d8-9671-f3ec0d75de3d · outbound

This paper cites Efficient hybrid oversampling and intelligent undersampling for imbalanced big data classification.

Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Efficient hybrid oversampling and intelligent undersampling for imbalanced big data classification

Reference 24

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data kNN approach to unbalanced data distributions: a case study involving information extraction

Reference 25

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Foundations of data imbalance and solutions for a data democracy

Reference 26

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data SMOTE: Synthetic Minority Over-sampling Technique

Reference 27

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Wang, Stefanka S

Reference 28

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Enhancing and improving the performance of imbalanced class data using novel GBO and SSG: A comparative analysis

Reference 29

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Garcia, and Shutao Li

Reference 30

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data KNNOR: An over- sampling technique for imbalanced datasets

Reference 31

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Wang, Stefanka S

Reference 32

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data R-WDLS: An efficient security region oversampling technique based on data distribution

Reference 33

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Pereira, Anabela Afonso, and Fátima Melo Medeiros

Reference 34

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data A comprehensive comparison among metaheuristics (MHs) for geohazard modeling using machine learning: Insights from a case study of landslide displacement prediction

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Hybrid Firefly Optimised Ensemble Classification for Drift- ing Data Streams with Imbalance

Reference 36

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Mawuli, Qinli Yang, and Junming Shao

Reference 37

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Statistical comparisons of classifiers over multiple data sets

Reference 38

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Electricity theft detection with automatic labeling and enhanced rusboost classification using differ- ential evolution and jaya algorithm

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Resampling imbalanced data for network intrusion detection datasets

Reference 40

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data Improved multi-class classification approach for imbalanced big data on spark

Reference 41

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data doi:10.1177/1550147720916404

Reference 2020

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Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data doi:10.1016/j.ipm.2022.103235

Reference 2023

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