search for: luk111111

Dear all, we are trying to model some data from rare plants so we always have less than 50 1x1 km presences, and the total area is about 550.000 square km. So we have a real problem, when we perform a GAM, if we consider only the same amount of absences than presences. We have thought to use a greater number of absences but in this case we shoud downweight them. Does anybody know how to use the

1. According to the doc of PAMR, the shrinkage threshold is determined by cross-validation. Does this mean that user need not tune any parameter? 2. I tried two applications using PAMR, the results are very disappointing. The attached are the cross-validation results. You can see that the classification errors are relatively high (0.2 at the best), in the case of two categories classification,

I used the following command to train a randomForest model train.rf <- randomForest(grp ~ ., data=tr, ntree=100, mtry=50) My question is how to save the trained model so that it can be loaded later for testing new samples? Thanks, Luk --------------------------------- [[alternative HTML version deleted]]