D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Mathematics D-index 38 Citations 224,947 72 World Ranking 1513 National Ranking 672

Research.com Recognitions

Awards & Achievements

2002 - Wald Memorial Lecturer

2001 - Member of the National Academy of Sciences

1987 - Fellow of the American Statistical Association (ASA)

Overview

What is he best known for?

The fields of study Leo Breiman is best known for:

  • Statistics
  • Regression analysis
  • Machine learning

Leo Breiman performs multidisciplinary studies into Statistics and Applied mathematics in his work. As part of his studies on Artificial intelligence, Leo Breiman often connects relevant areas like Classifier (UML). Leo Breiman combines Regression analysis and Linear regression in his research. Leo Breiman performs multidisciplinary study on Linear regression and Regression analysis in his works. His work on Selection (genetic algorithm) is being expanded to include thematically relevant topics such as Machine learning. His research combines Selection (genetic algorithm) and Machine learning. His research on Programming language frequently connects to adjacent areas such as Set (abstract data type). His study on Set (abstract data type) is mostly dedicated to connecting different topics, such as Programming language. He connects Econometrics with Statistics in his study.

His most cited work include:

  • None (71327 citations)
  • Bagging predictors (10128 citations)
  • Classification and Regression Trees. (7432 citations)

What are the main themes of his work throughout his whole career to date

His Artificial intelligence study frequently draws parallels with other fields, such as Class (philosophy) and Pattern recognition (psychology). In his works, he conducts interdisciplinary research on Statistics and Linear regression. Leo Breiman combines Econometrics and Regression analysis in his research. In his work, he performs multidisciplinary research in Regression analysis and Econometrics. In his articles, he combines various disciplines, including Machine learning and Statistics. In his research, Leo Breiman undertakes multidisciplinary study on Algorithm and Artificial intelligence. His Programming language study frequently links to adjacent areas such as Set (abstract data type). As part of his studies on Set (abstract data type), Leo Breiman often connects relevant subjects like Programming language.

Leo Breiman most often published in these fields:

  • Statistics (74.32%)
  • Artificial intelligence (45.95%)
  • Regression (33.78%)

What were the highlights of his more recent work (between 2002-2018)?

  • Statistics (60.00%)
  • Artificial intelligence (60.00%)
  • Regression (40.00%)

In recent works Leo Breiman was focusing on the following fields of study:

His research ties Regression and Statistics together. Borrowing concepts from Boosting (machine learning), he weaves in ideas under Artificial intelligence. Many of his studies involve connections with topics such as Sigmoid function and Machine learning. With his scientific publications, his incorporates both Econometrics and Statistics. His research on Population frequently connects to adjacent areas such as Demography. His research on Demography frequently links to adjacent areas such as Population. He integrates many fields in his works, including Operating system and Polling. Leo Breiman undertakes multidisciplinary studies into Polling and Operating system in his work. Combinatorics is closely attributed to Tree (set theory) in his research.

Between 2002 and 2018, his most popular works were:

  • Classification And Regression Trees (1147 citations)
  • Population theory for boosting ensembles (75 citations)
  • Random Forests: Finding Quasars (44 citations)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Random Forests

Leo Breiman.
Machine Learning archive (2001)

91971 Citations

Classification and regression trees

Leo Breiman.
(1983)

53450 Citations

Bagging predictors

Leo Breiman.
Machine Learning archive (1996)

29023 Citations

Classification and Regression Trees.

John Van Ryzin;Leo Breiman;Jerome H. Friedman;Richard A. Olshen.
Journal of the American Statistical Association (1986)

26385 Citations

Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)

Leo Breiman.
Statistical Science (2001)

4383 Citations

Estimating Optimal Transformations for Multiple Regression and Correlation.

Leo Breiman;Jerome H. Friedman.
Journal of the American Statistical Association (1985)

2415 Citations

Arcing classifier (with discussion and a rejoinder by the author)

Leo Breiman.
Annals of Statistics (1998)

2025 Citations

Statistical modeling: The two cultures

Leo Breiman.
Quality Engineering (2001)

1936 Citations

Stacked regressions

Leo Breiman.
Machine Learning archive (1996)

1822 Citations

Heuristics of instability and stabilization in model selection

Leo Breiman.
Annals of Statistics (1996)

1580 Citations

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