T
Trevor Hastie
Researcher at Stanford University
Publications - 428
Citations - 230646
Trevor Hastie is an academic researcher from Stanford University. The author has contributed to research in topics: Lasso (statistics) & Feature selection. The author has an hindex of 124, co-authored 412 publications receiving 202592 citations. Previous affiliations of Trevor Hastie include University of Waterloo & University of Toronto.
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Journal ArticleDOI
Presence-only data and the em algorithm.
TL;DR: An expectation-maximization algorithm is proposed to estimate the underlying presence-absence logistic model for presence-only data and it is shown that the population prevalence of a species is only identifiable when there is some unrealistic constraint on the structure of theLogistic model.
Journal Article
Boosting as a Regularized Path to a Maximum Margin Classifier
TL;DR: It is built on recent work by Efron et al. to show that boosting approximately (and in some cases exactly) minimizes its loss criterion with an l1 constraint on the coefficient vector, and shows that as the constraint is relaxed the solution converges (in the separable case) to an "l1-optimal" separating hyper-plane.
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Meta-analysis of Trials Comparing β-Blockers, Calcium Antagonists, and Nitrates for Stable Angina
Paul A. Heidenreich,Kathryn M. McDonald,Trevor Hastie,Bahaa M. Fadel,Vivian Hagan,Byron K. Lee,Mark A. Hlatky +6 more
TL;DR: β-Blockers provide similar clinical outcomes and are associated with fewer adverse events than calcium antagonists in randomized trials of patients who have stable angina in a comparison of relative efficacy and tolerability in antianginal drugs.
Journal ArticleDOI
Causal Interpretations of Black-Box Models
Qingyuan Zhao,Trevor Hastie +1 more
TL;DR: The possibility of extracting causal interpretations from black-box machine-trained models, and three requirements to make causal interpretations: a model with good predictive performance, some domain knowledge in the form of a causal diagram and suitable visualization tools.
Journal ArticleDOI
Genetics of 35 blood and urine biomarkers in the UK Biobank
Nasa Sinnott-Armstrong,Nasa Sinnott-Armstrong,Nasa Sinnott-Armstrong,Yosuke Tanigawa,David Amar,David Amar,Nina Mars,Christian Benner,Matthew Aguirre,Guhan Venkataraman,Michael Wainberg,Hanna Ollila,Hanna Ollila,Hanna Ollila,Tuomo Kiiskinen,Tuomo Kiiskinen,Aki S. Havulinna,Aki S. Havulinna,James P. Pirruccello,James P. Pirruccello,Junyang Qian,Anna Shcherbina,Anna Shcherbina,FinnGen,Fatima Rodriguez,Themistocles L. Assimes,Themistocles L. Assimes,Vineeta Agarwala,Robert Tibshirani,Trevor Hastie,Samuli Ripatti,Samuli Ripatti,Jonathan K. Pritchard,Mark J. Daly,Mark J. Daly,Mark J. Daly,Manuel A. Rivas +36 more
TL;DR: In this article, the genetic basis of 35 blood and urine laboratory measurements in the UK Biobank (n = 363,228 individuals) was evaluated and the results delineate the genetic underlying of biomarkers and their causal influences on diseases and improve genetic risk stratification for common diseases.