Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction
Top Cited Papers
- 15 March 2006
- journal article
- research article
- Published by Springer Nature in Ecosystems
- Vol. 9 (2) , 181-199
- https://doi.org/10.1007/s10021-005-0054-1
Abstract
No abstract availableKeywords
This publication has 47 references indexed in Scilit:
- SmcHD1, containing a structural-maintenance-of-chromosomes hinge domain, has a critical role in X inactivationNature Genetics, 2008
- Random Forest: A Classification and Regression Tool for Compound Classification and QSAR ModelingJournal of Chemical Information and Computer Sciences, 2003
- The support vector machine under testNeurocomputing, 2003
- Analyzing baggingThe Annals of Statistics, 2002
- Potential redistribution of tree species habitat under five climate change scenarios in the eastern USForest Ecology and Management, 2002
- Boosting the margin: a new explanation for the effectiveness of voting methodsThe Annals of Statistics, 1998
- Why Trees Migrate So Fast: Confronting Theory with Dispersal Biology and the PaleorecordThe American Naturalist, 1998
- Predicting the distribution of shrub species in southern California from climate and terrain‐derived variablesJournal of Vegetation Science, 1998
- Classification trees: an alternative to traditional land cover classifiersInternational Journal of Remote Sensing, 1996
- Multivariate Adaptive Regression SplinesThe Annals of Statistics, 1991