search for: t_feb

.... I have used a training dataset to train the model, and tested it against a validation data set with good results: AUC is high, and the confusion matrix indicates low commission and omission errors. The code for the best-fit model is: svm.model <-svm(as.factor(acutus)~p_feb+p_jan+p_mar+p_sep+t_feb+t_july+t_june+t_mar,cost=10000, gamma=1, probability=T) Because ultimately I want to create prediction maps of probabilities of species occurrence under future climate change, I want to use the results of the validated model to predict probability of presence using data describing future condition...