Resampling strategies for imbalanced regression: a survey and empirical analysis | Paper Citation Record

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This paper cites Expert systems with applications 73, 220–239 (2017).

Resampling strategies for imbalanced regression: a survey and empirical analysis Expert systems with applications 73, 220–239 (2017)

Reference 1

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This paper cites Progress in Artificial Intelligence 5(4), 221–232 (2016).

Resampling strategies for imbalanced regression: a survey and empirical analysis Progress in Artificial Intelligence 5(4), 221–232 (2016)

Reference 2

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This paper cites Journal of Big Data 6(1), 1–54 (2019).

Resampling strategies for imbalanced regression: a survey and empirical analysis Journal of Big Data 6(1), 1–54 (2019)

Reference 3

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Resampling strategies for imbalanced regression: a survey and empirical analysis UBL: an R package for Utility-based Learning

Reference 4

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This paper cites In: First International Workshop on Learning with Imbalanced Domains: Theory and Applications, vol.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: First International Workshop on Learning with Imbalanced Domains: Theory and Applications, vol

Reference 5

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Resampling strategies for imbalanced regression: a survey and empirical analysis Unresolved cited work

Reference 6

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This paper cites Knowledge-Based Systems 119, 232–256 (2017).

Resampling strategies for imbalanced regression: a survey and empirical analysis Knowledge-Based Systems 119, 232–256 (2017)

Reference 7

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This paper cites Machine Learning 109(9), 1803–1835 (2020).

Resampling strategies for imbalanced regression: a survey and empirical analysis Machine Learning 109(9), 1803–1835 (2020)

Reference 8

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This paper cites In: Portuguese Conference on Artificial Intelligence, pp.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: Portuguese Conference on Artificial Intelligence, pp

Reference 9

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This paper cites Neurocomputing 343, 76–99 (2019).

Resampling strategies for imbalanced regression: a survey and empirical analysis Neurocomputing 343, 76–99 (2019)

Reference 10

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This paper cites In: ICSOFT, pp.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: ICSOFT, pp

Reference 11

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This paper cites IEEE Transactions on Reliability 69(4), 1355–1375 (2020).

Resampling strategies for imbalanced regression: a survey and empirical analysis IEEE Transactions on Reliability 69(4), 1355–1375 (2020)

Reference 12

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This paper cites Expert Systems with Applications 82, 357–382 (2017).

Resampling strategies for imbalanced regression: a survey and empirical analysis Expert Systems with Applications 82, 357–382 (2017)

Reference 13

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This paper cites Journal of Chemical Information and Modeling 60(8), 4098–4107 (2020).

Resampling strategies for imbalanced regression: a survey and empirical analysis Journal of Chemical Information and Modeling 60(8), 4098–4107 (2020)

Reference 14

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This paper cites Toxics 9(12), 333 (2021).

Resampling strategies for imbalanced regression: a survey and empirical analysis Toxics 9(12), 333 (2021)

Reference 15

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Resampling strategies for imbalanced regression: a survey and empirical analysis In: International Conference on Discovery Science, pp

Reference 16

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This paper cites Expert Systems with Applications 158, 113026 (2020).

Resampling strategies for imbalanced regression: a survey and empirical analysis Expert Systems with Applications 158, 113026 (2020)

Reference 17

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This paper cites Applied Soft Computing 83, 105662 (2019).

Resampling strategies for imbalanced regression: a survey and empirical analysis Applied Soft Computing 83, 105662 (2019)

Reference 18

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This paper cites Foundations of Computing and Decision Sciences 42(2), 149–176 (2017).

Resampling strategies for imbalanced regression: a survey and empirical analysis Foundations of Computing and Decision Sciences 42(2), 149–176 (2017)

Reference 19

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This paper cites Neurocomput- ing 286, 179–192 (2018) 42.

Resampling strategies for imbalanced regression: a survey and empirical analysis Neurocomput- ing 286, 179–192 (2018) 42

Reference 20

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This paper cites International Journal of Engineering & Technology 8, 390–397 (2019).

Resampling strategies for imbalanced regression: a survey and empirical analysis International Journal of Engineering & Technology 8, 390–397 (2019)

Reference 21

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This paper cites In: 2015 IEEE Trustcom/BigDataSE/ISPA, vol.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: 2015 IEEE Trustcom/BigDataSE/ISPA, vol

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This paper cites Information Sciences 325, 98–117 (2015).

Resampling strategies for imbalanced regression: a survey and empirical analysis Information Sciences 325, 98–117 (2015)

Reference 23

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This paper cites Knowledge-Based Systems 227, 107222 (2021).

Resampling strategies for imbalanced regression: a survey and empirical analysis Knowledge-Based Systems 227, 107222 (2021)

Reference 24

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This paper cites International Journal of Pattern Recognition and Artificial Intelligence 33(11), 1940009 (2019).

Resampling strategies for imbalanced regression: a survey and empirical analysis International Journal of Pattern Recognition and Artificial Intelligence 33(11), 1940009 (2019)

Reference 25

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This paper cites Pattern Recognition 57, 164–178 (2016).

Resampling strategies for imbalanced regression: a survey and empirical analysis Pattern Recognition 57, 164–178 (2016)

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This paper cites A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework.

Resampling strategies for imbalanced regression: a survey and empirical analysis A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework

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This paper cites In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp

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This paper cites ACM Computing Surveys (CSUR) 49(2), 1–50 (2016).

Resampling strategies for imbalanced regression: a survey and empirical analysis ACM Computing Surveys (CSUR) 49(2), 1–50 (2016)

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Resampling strategies for imbalanced regression: a survey and empirical analysis Mathematics of Computation 52(186), 471–494 (1989)

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Resampling strategies for imbalanced regression: a survey and empirical analysis Unresolved cited work

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This paper cites Computational statistics & data analysis 52(12), 5186–5201 (2008).

Resampling strategies for imbalanced regression: a survey and empirical analysis Computational statistics & data analysis 52(12), 5186–5201 (2008)

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Resampling strategies for imbalanced regression: a survey and empirical analysis SIAM 43 Journal on Numerical Analysis 17(2), 238–246 (1980)

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This paper cites IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 42(4), 463–484 (2011).

Resampling strategies for imbalanced regression: a survey and empirical analysis IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 42(4), 463–484 (2011)

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Resampling strategies for imbalanced regression: a survey and empirical analysis Information sciences 250, 113–141 (2013)

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This paper cites In: Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, pp.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, pp

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This paper cites In: 2018 IEEE 5th International Con- ference on Data Science and Advanced Analytics (DSAA), pp.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: 2018 IEEE 5th International Con- ference on Data Science and Advanced Analytics (DSAA), pp

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This paper cites In: Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, vol.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, vol

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This paper cites In: European Conference on Principles of Data Mining and Knowledge Discovery, pp.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: European Conference on Principles of Data Mining and Knowledge Discovery, pp

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This paper cites In: International Conference on Machine Learning, pp.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: International Conference on Machine Learning, pp

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This paper cites Machine Learning 110, 2187–2211 (2021).

Resampling strategies for imbalanced regression: a survey and empirical analysis Machine Learning 110, 2187–2211 (2021)

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This paper cites Journal of artificial intelligence research 16, 321–357 (2002).

Resampling strategies for imbalanced regression: a survey and empirical analysis Journal of artificial intelligence research 16, 321–357 (2002)

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This paper cites Expert Systems with Applications, 116387 (2022).

Resampling strategies for imbalanced regression: a survey and empirical analysis Expert Systems with Applications, 116387 (2022)

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This paper cites : Addressing the curse of imbalanced training sets: one-sided selection.

Resampling strategies for imbalanced regression: a survey and empirical analysis : Addressing the curse of imbalanced training sets: one-sided selection

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This paper cites ACM SIGKDD explorations 44 newsletter 6(1), 20–29 (2004).

Resampling strategies for imbalanced regression: a survey and empirical analysis ACM SIGKDD explorations 44 newsletter 6(1), 20–29 (2004)

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This paper cites Computational Statistics 14(2), 277–292 (1999).

Resampling strategies for imbalanced regression: a survey and empirical analysis Computational Statistics 14(2), 277–292 (1999)

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This paper cites Computational statistics & data analysis 34(2), 165–191 (2000).

Resampling strategies for imbalanced regression: a survey and empirical analysis Computational statistics & data analysis 34(2), 165–191 (2000)

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This paper cites In: Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, pp.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, pp

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This paper cites Data Mining and Knowledge Discovery 35, 2389–2466 (2021).

Resampling strategies for imbalanced regression: a survey and empirical analysis Data Mining and Knowledge Discovery 35, 2389–2466 (2021)

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This paper cites In: International Symposium on Intelligent Data Analysis, pp.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: International Symposium on Intelligent Data Analysis, pp

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This paper cites In: European Conference on Prin- ciples of Data Mining and Knowledge Discovery, pp.

Resampling strategies for imbalanced regression: a survey and empirical analysis In: European Conference on Prin- ciples of Data Mining and Knowledge Discovery, pp

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This paper cites International Journal of Data Science and Analytics 3(3), 161–181 (2017).

Resampling strategies for imbalanced regression: a survey and empirical analysis International Journal of Data Science and Analytics 3(3), 161–181 (2017)

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:04:15.212491Z

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Observation d8ade955-128f-4d6d-aed8-b4635a33a733 · outbound

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Resampling strategies for imbalanced regression: a survey and empirical analysis Unresolved cited work

Reference 53

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Observation 31921ac2-b634-4ae1-8fec-a37cf1e49f8b · outbound

This paper cites Journal of Machine Learning Research 7(Jan), 1–30 (2006).

Resampling strategies for imbalanced regression: a survey and empirical analysis Journal of Machine Learning Research 7(Jan), 1–30 (2006)

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:04:14.867861Z

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Observation 9bda4b57-07c8-441e-84f0-ed54f850d6bc · outbound

This paper cites Machine Learning107(1), 209– 246 (2018) 45.

Resampling strategies for imbalanced regression: a survey and empirical analysis Machine Learning107(1), 209– 246 (2018) 45

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:04:14.819447Z

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