Random forests for classification in ecology (Record no. 51076)

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control field MX-MdCICY
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250625160200.0
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Transcribing agency CICY
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Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) B-16911
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245 10 - TITLE STATEMENT
Title Random forests for classification in ecology
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Volume/sequential designation Ecology, 88, p.2783-2792, 2007
520 3# - SUMMARY, ETC.
Summary, etc. Classification procedures are some of the most widely used statistical methods in ecology. Random forests (RF)is a new and powerful statistical classifier that is well established in other disciplines but is relatively unknown in ecology. Advantages of RF compared to other statistical classifiers include (1)very high classification accuracy; (2)a novel method of determining variable importance; (3)ability to model complex interactions among predictor variables; (4)flexibility to perform several types of statistical data analysis, including regression, classification, survival analysis, and unsupervised learning; and (5)an algorithm for imputing missing values. We compared the accuracies of RF and four other commonly used statistical classifiers using data on invasive plant species presence in Lava Beds National Monument, California, USA, rare lichen species presence in the Pacific Northwest, USA, and nest sites for cavity nesting birds in the Uinta Mountains, Utah, USA. We observed high classification accuracy in all applications as measured by cross-validation and, in the case of the lichen data, by independent test data, when comparing RF to other common classification methods. We also observed that the variables that RF identified as most important for classifying invasive plant species coincided with expectations based on the literature.
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Topical term or geographic name entry element ADDITIVE LOGISTIC REGRESSION
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Topical term or geographic name entry element CLASSIFICATION TREES
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Topical term or geographic name entry element LDA
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Topical term or geographic name entry element LOGISTIC REGRESSION
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element MACHINE LEARNING
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Topical term or geographic name entry element PARTIAL DEPENDENCE PLOTS
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Topical term or geographic name entry element RANDOM FORESTS
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Topical term or geographic name entry element SPECIES DISTRIBUTION MODELS
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Cutler, D. Richard
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Edwards Jr., Thomas C.
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Personal name Beard, Karen H.
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Cutler, Adele
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Hess, Kyle T.
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Gibson, Jacob
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Lawler, Joshua J.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://drive.google.com/file/d/1A03Nq7vvoWl1RihizPFvdITi03jrU4WD/view?usp=drivesdk">https://drive.google.com/file/d/1A03Nq7vvoWl1RihizPFvdITi03jrU4WD/view?usp=drivesdk</a>
Public note Para ver el documento ingresa a Google con tu cuenta: @cicy.edu.mx
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Source of classification or shelving scheme Clasificación local
Koha item type Documentos solicitados
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Lost status Source of classification or shelving scheme Damaged status Not for loan Collection Home library Current library Shelving location Date acquired Total checkouts Full call number Date last seen Price effective from Koha item type
  Clasificación local     Ref1 CICY CICY Documento préstamo interbibliotecario 25.06.2025   B-16911 25.06.2025 25.06.2025 Documentos solicitados