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Topic · Artificial Intelligence

Imbalanced Data Classification Techniques

Imbalanced Data Classification Techniques is a research topic within Artificial Intelligence. Science Explorer counts 21k research works in it since 1954. 27.8% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the challenges and techniques for handling imbalanced data in classification problems. It covers methods such as SMOTE, ROC analysis, cost-sensitive learning, ensemble methods, and their applications in fraud detection. The cluster also discusses the use of precision-recall and boosting algorithms, as well as the effectiveness of random forest in addressing imbalanced datasets.

  • Imbalanced Data
  • Classification
  • SMOTE
  • ROC Analysis
  • Cost-Sensitive Learning
  • Ensemble Methods
  • Fraud Detection
  • Precision-Recall
  • Boosting
  • Random Forest
Research works
21k
fractional, since 1954
In the world top 10%
5.9k
per year above
Top-10% rate
27.8%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+109%
the tick is no change

Which countries lead Imbalanced Data Classification Techniques research?

By volume, China and India publish the most (1.7k and 1.7k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 1.7k works
  2. 2 India 1.7k works
  3. 3 United States 775 works
  4. 4 Indonesia 405 works
  5. 5 Türkiye 211 works
  6. 6 Brazil 195 works
  7. 7 United Kingdom 184 works
  8. 8 Bangladesh 128 works
  9. 9 ?? 126 works
  10. 10 Malaysia 122 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 30.7%India: 30.3%United States: 14.1%Indonesia: 7.4%6 others listed: 17.5%31%largest
China1,686 · 30.7%India1,668 · 30.3%United States775 · 14.1%Indonesia405 · 7.4%6 others listed965 · 17.5%

Shares of the rows listed above, not of the whole node.

Which institutions lead Imbalanced Data Classification Techniques research?

By volume in 2022–2025, Saveetha University publishes the most Imbalanced Data Classification Techniques research, followed by SRM Institute of Science and Technology and Vellore Institute of Technology University.

By volume, 2022–2025

  1. 1 Saveetha UniversityIndia 100 works
  2. 2 SRM Institute of Science and TechnologyIndia 45 works
  3. 3 Vellore Institute of Technology UniversityIndia 41 works
  4. 4 Binus UniversityIndonesia 40 works
  5. 5 Chandigarh UniversityIndia 39 works
  6. 6 Amrita Vishwa VidyapeethamIndia 31 works
  7. 7 Koneru Lakshmaiah Education FoundationIndia 25 works
  8. 8 Chitkara UniversityIndia 24 works
  9. 9 Sepuluh Nopember Institute of TechnologyIndonesia 23 works
  10. 10 Symbiosis International UniversityIndia 23 works

Who are the leading researchers in Imbalanced Data Classification Techniques?

The most-cited researchers publishing on Imbalanced Data Classification Techniques include Philip S. Yu, Francisco Herrera and Dacheng Tao.

  1. 1 Philip S. Yu United States 6.6k citations
  2. 2 Francisco Herrera Spain 6.5k citations
  3. 3 Dacheng Tao Australia 6.1k citations
  4. 4 Witold Pedrycz Canada 5.4k citations
  5. 5 Jiawei Han United States 5.2k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Imbalanced Data Classification Techniques research done?

The largest centres of Imbalanced Data Classification Techniques research in 2022–2025 are Beijing (China), Chennai (India), Shanghai (China) and Bengaluru (India). Among places with at least 20 works in it, it is an unusually large share of all research in Boca Raton, Vijayawada and Greater Noida.

Largest cities, 2022–2025

  1. 1 Beijing China 280 works
  2. 2 Chennai India 247 works
  3. 3 Shanghai China 128 works
  4. 4 Bengaluru India 91 works
  5. 5 Chengdu China 91 works
  6. 6 Dhaka Bangladesh 86 works
  7. 7 Nanjing China 85 works
  8. 8 Guangzhou China 79 works
  9. 9 Pune India 77 works
  10. 10 Xi'an China 76 works

Where it is the local speciality

  1. Boca RatonUS · 22.5 works15×
  2. VijayawadaIN · 36.4 works10×
  3. Greater NoidaIN · 42.1 works8.8×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Imbalanced Data Classification Techniques than the world average.

See Imbalanced Data Classification Techniques on the map

Where is the best place to study Imbalanced Data Classification Techniques?

Among universities, judged by research, Koneru Lakshmaiah Education Foundation, Florida Atlantic University and Southwestern University of Finance and Economics score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 31.16%fractional works in this node (log) →share in the world top 10% →Koneru Lakshmaiah Education Foundation: 25, 29.5%Florida Atlantic University: 22, 35.3%Southwestern University of Finance and Economics: 12, 30.5%Saveetha University: 100, 8.2%National Institute of Technology Raipur: 9, 43.5%SRM University: 13, 45.4%Vellore Institute of Technology University: 41, 26.6%Chandigarh University: 39, 22.7%University of the Cumberlands: 10, 36.2%Amrita Vishwa Vidyapeetham: 31, 33.7%Florida Atlantic Uni…Southwestern Univers…Koneru Lakshmaiah Ed…Saveetha University
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Koneru Lakshmaiah Education FoundationIndia 63.029.5%11.4×25 +662.2%
2 Florida Atlantic UniversityUnited States 56.535.3%17.0×22 +59.6%
3 Southwestern University of Finance and EconomicsChina 56.430.5%10.8×12 +168.2%
4 Saveetha UniversityIndia 56.08.2%13.6×100 —
5 National Institute of Technology RaipurIndia 55.443.5%8.5×9 +190.9%
6 SRM UniversityIndia 53.545.4%9.1×13 —
7 Vellore Institute of Technology UniversityIndia 52.926.6%5.5×41 +242.7%
8 Chandigarh UniversityIndia 52.122.7%9.2×39 —
9 University of the CumberlandsUnited States 51.336.2%29.9×10 —
10 Amrita Vishwa VidyapeethamIndia 50.433.7%7.6×31 —

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Imbalanced Data Classification Techniques research growing?

Output in 2018–2022 was 109% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Imbalanced Data Classification Techniques.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.