Modelling the potential distribution of an invasive mosquito species: comparative evaluation of four machine learning methods and their combinations
Günter A. Schaub,
Doreen Walther and
Ecological Modelling, 2018, vol. 388, issue C, 136-144
We tested four machine learning methods for their performance in the classification of mosquito species occurrence related to weather variables: support vector machine, random forest, logistic regression and decision tree. The objective was to find a method which showed the most accurate model for the prediction of the potential geographical distribution of Aedes japonicus japonicus, an invasive mosquito species in Germany.
Keywords: Decision tree; Logistic regression; Random forest; Support vector machine; Hasse diagram technique; Aedes japonicus japonicus (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:388:y:2018:i:c:p:136-144
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