Resampling Methods for Evaluating Classification Accuracy of Wildlife Habitat Models
Predictive models of wildlife-habitat relationships often have been developed without being tested The
apparent classification accuracy of such models can be optimistically biased and misleading. Data resampling methods exist that yield a more realistic estimate of model classification accuracy. These methods are simple and require no new sample data. We illustrate these methods (cross-validation.
jackknife resampling, and bootstrap resampling) with computer simulation to demonstrate the increase in precision of the estimate. The bootstrap method is then applied to field data as a technique for model comparison We recommend that biologists use some resampling procedure to evaluatewildlife habitat models prior to field evaluation.
Credits: Environmental Management Vol 13, No 6, pp 783-787
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