Concepedia

Gradient Boosting

Gradient Boosting is a machine learning ensemble method that iteratively combines weak predictive models, typically decision trees, by sequentially minimizing a loss function through gradient descent, with each subsequent model correcting the residual errors of its predecessor.

4K

Publications

286.1K

Citations

17.1K

Authors

4.4K

Institutions

Publications per year

2017–2026

3.6K

Parents

Publications

4K

XGBoost

2016 · 48.6K citations · Full text

, , +15

Greedy function approximation: A gradient boosting machine.

Jerome H. Friedman · The Annals of Statistics · 2001 · 29K citations · Full text

, , +17

A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting

Yoav Freund, Robert E. Schapire · Journal of Computer and System Sciences · 1997 · 20.3K citations

, , +14

LightGBM: A Highly Efficient Gradient Boosting Decision Tree

Guolin Ke, Qi Meng, Thomas Finley et al. · HAL (Le Centre pour la Communication Scientifique Directe) · 2017 · 9.5K citations · Full text

, , +16

XGBoost: A Scalable Tree Boosting System

arXiv (Cornell University) · 2016 · 7.1K citations · Full text

, , +16

1–5 of 4K

Authors

17.1K

  1. RE
    Robert E. Schapire

    AT&T (United States), United States

    12 publications · 25.2K citations

    11

    h-index

  2. MN
    Muhammad Nasir Amin

    King Faisal University, Saudi Arabia

    11 publications · 445 citations

    11

    h-index

  3. KK
    Kaffayatullah Khan

    King Faisal University, Saudi Arabia

    11 publications · 445 citations

    11

    h-index

  4. AM
    Andreas Mayr

    Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

    10 publications · 1.2K citations

    10

    h-index

  5. IA
    Imran Ashraf

    Yeungnam University, South Korea

    10 publications · 436 citations

    10

    h-index

1–5 of 17.1K

Institutions

4.4K

  1. Chinese Academy of Sciences

    Beijing, China

    33 h-index

    228 publications

    20K citations

  2. Central South University

    Changsha, China

    28 h-index

    161 publications

    10.7K citations

  3. University of Chinese Academy of Sciences

    Beijing, China

    27 h-index

    118 publications

    5.9K citations

  4. Peking University

    Beijing, China

    26 h-index

    100 publications

    4.5K citations

  5. Wuhan University

    Wuhan, China

    26 h-index

    101 publications

    4.3K citations

  6. Tsinghua University

    Beijing, China

    25 h-index

    72 publications

    4.8K citations

  7. Zhejiang University

    Hangzhou, China

    24 h-index

    117 publications

    9.8K citations

  8. Shanghai Jiao Tong University

    Shanghai, China

    24 h-index

    105 publications

    4.2K citations

1–8 of 4.4K

Venues

  1. IEEE Access

    120 publications · 10K citations

    52

    h-index

  2. Scientific Reports

    128 publications · 7.1K citations

    45

    h-index

  3. Remote Sensing

    74 publications · 3.5K citations

    35

    h-index

  4. Sensors

    55 publications · 2.2K citations

    29

    h-index

  5. PLoS ONE

    55 publications · 2.5K citations

    29

    h-index

1–5