About: Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction

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article by Anantha M. Prasad et al published March 2006 in Ecosystems

Attributes	Values
rdf:type	Item
description	wetenschappelijk artikel (nl) article scientifique publié en 2006 (fr) наукова стаття, опублікована в березні 2006 (uk) im März 2006 veröffentlichter wissenschaftlicher Artikel (de) article by Anantha M. Prasad et al published March 2006 in Ecosystems (en)
publication date	wds:Q56221737-1D7CC894-3A66-45ED-A2B5-E15A19F6E4F8
publication date	2006-03-01 00:00:00Z (xsd:dateTime)
exact match	wds:Q56221737-EDB2B3BE-E224-4C88-AFD4-C1B9D15A4246
exact match	https://scigraph.springernature.com/pub.10.1007/s10021-005-0054-1
cites work	wds:Q56221737-0C84EB0B-C57F-42B5-A97B-C54EFBA2CD6C wds:Q56221737-8B335DCC-C00A-4394-8478-2FF057E23911
cites work	Random forest: a classification and regression tool for compound classification and QSAR modeling. Predicting Invasions of Woody Plants Introduced into North America. Prediccion de Invasiones de Plantas Lenosas Introducidas a Norteamerica
author name string	wds:Q56221737-E6C52E4B-0475-4A33-BB6C-81A5C014BE84 wds:Q56221737-FA1ABBF4-E7E8-40C3-9A53-6D26CC940979
author name string	Andy Liaw Anantha M. Prasad
rdfs:label	Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction (en) Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction (nl)
skos:prefLabel	Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction (en) Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction (nl)
name	Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction (en) Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction (nl)
author	wds:Q56221737-0311E8C2-0DF6-4346-BBFF-734F1B7E013F
author	Louis R. Iverson
title	wds:Q56221737-14C453B1-CE58-4D32-BC62-F624539AA520
title	Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction (en)
page(s)	wds:Q56221737-D1A2000E-7CF2-464E-A6C1-B7D883727F93
page(s)	181-199
instance of	wds:Q56221737-ADF2E5DA-B9CB-49A6-9D2B-2506DAAA3B12
instance of	scholarly article
main subject	wds:Q56221737-F6B5B953-FCB3-4EDF-A6B2-E67053F96AF5
main subject	random forest
published in	wds:Q56221737-EAF96EA0-35F6-4298-A818-D224A44F4C3A
published in	Ecosystems
issue	wds:Q56221737-7A23CF62-A57F-43B1-B0E5-BE016A7B8D0A
volume	wds:Q56221737-408B7AEA-9ED8-4D39-ADE5-6E9B0670782C
issue	2
volume	9
DOI	wds:Q56221737-9E133F21-2CE4-4C04-8C43-6EFE155F6CBF
DOI	http://dx.doi.org/10.1007/S10021-005-0054-1
DOI	10.1007/S10021-005-0054-1
maintained by WikiProject	wds:Q56221737-64A083E6-1CEB-45E4-A06E-723A9D0B8FEB
maintained by WikiProject	WikiProject Ecology
ResearchGate publication ID	wds:Q56221737-8A9171FB-5181-4C28-8FBD-1753FC0252D0
ResearchGate publication ID	225909333
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q56221737
is cites work of	Global patterns and predictions of seafloor biomass using random forests Decomposing environmental, spatial, and spatiotemporal components of species distributions Why choose Random Forest to predict rare species distribution with few samples in large undersampled areas? Three Asian crane species models provide supporting evidence Regional distribution models with lack of proximate predictors: Africanized honeybees expanding north Effects of spatial scale and choice of statistical model (linear versus tree-based) on determining species–habitat relationships Economic conditions predict prevalence of West Nile virus Predicting invertebrate herbivory from plant traits: evidence from 51 grassland species in experimental monocultures Spatially explicit predictions of blood parasites in a widely distributed African rainforest bird. Composition of epiphytic bacterial communities differs on petals and leaves Method selection for species distribution modelling: are temporally or spatially independent evaluations necessary? Drivers and hotspots of extinction risk in marine mammals Exploring the ecological processes driving geographical patterns of breeding bird richness in British Columbia, Canada A comprehensive global 5 min resolution land-use data set for the year 2000 consistent with national census data Projecting invasion risk of non-native watersnakes (Nerodia fasciata and Nerodia sipedon) in the western United States Testing the predictive performance of distribution models Intra-and-inter species biomass prediction in a plantation forest: testing the utility of high spatial resolution spaceborne multispectral RapidEye sensor and advanced machine learning algorithms Ecosystem assembly and terrestrial carbon balance under elevated CO(2). Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A. Predicting the conservation status of data-deficient species Floral odor bouquet loses its ant repellent properties after inhibition of terpene biosynthesis Landscape-scale determinants of non-native fish communities From sensor data to animal behaviour: an oystercatcher example Better physical activity classification using smartphone acceleration sensor Mainland size variation informs predictive models of exceptional insular body size change in rodents Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates Spatial analysis of factors influencing long-term stress in the grizzly bear (Ursus arctos) population of Alberta, Canada Random forests for classification in ecology. Predictions of avian Plasmodium expansion under climate change Ecological forecasting and data assimilation in a data-rich era. The FIGS (focused identification of germplasm strategy) approach identifies traits related to drought adaptation in Vicia faba genetic resources Warning times for species extinctions due to climate change Regional scale patterns of fine root lifespan and turnover under current and future climate Mapping forest canopy height globally with spaceborne lidar Hydrometeorological variables predict fecal indicator bacteria densities in freshwater: data-driven methods for variable selection Forest restoration in a mixed-ownership landscape under climate change Correspondence of biological condition models of California streams at statewide and regional scales Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale Towards Quantitative Spatial Models of Seabed Sediment Composition Gradient forests: calculating importance gradients on physical predictors Species distribution modelling for conservation of an endangered endemic orchid. New trends in species distribution modelling Evaluating the effectiveness of conservation site networks under climate change: accounting for uncertainty. Spatiotemporal exploratory models for broad-scale survey data Predicting extinctions as a result of climate change Applying various algorithms for species distribution modelling Mapping migratory bird prevalence using remote sensing data fusion Explaining Accessibility and Satisfaction Related to Healthcare: A Mixed-Methods Approach Both topography and climate affected forest and woodland burn severity in two regions of the western US, 1984 to 2006 A Review of the Statistical and Quantitative Methods Used to Study Alcohol-Attributable Crime Microhabitat heterogeneity across leaves and flower organs promotes bacterial diversity. Mapping threats to power line corridors for Connecticut rights-of-way management Human population dynamics in Europe over the Last Glacial Maximum

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