2002 - Wald Memorial Lecturer
2001 - Member of the National Academy of Sciences
1987 - Fellow of the American Statistical Association (ASA)
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 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.
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.
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Machine Learning archive (2001)
Classification and regression trees
Machine Learning archive (1996)
Classification and Regression Trees.
John Van Ryzin;Leo Breiman;Jerome H. Friedman;Richard A. Olshen.
Journal of the American Statistical Association (1986)
Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)
Statistical Science (2001)
Estimating Optimal Transformations for Multiple Regression and Correlation.
Leo Breiman;Jerome H. Friedman.
Journal of the American Statistical Association (1985)
Arcing classifier (with discussion and a rejoinder by the author)
Annals of Statistics (1998)
Statistical modeling: The two cultures
Quality Engineering (2001)
Machine Learning archive (1996)
Heuristics of instability and stabilization in model selection
Annals of Statistics (1996)
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