Dear List, Please I have been implementing Random Forest in R for the to classify forest cover. I am doing it for 4 main classes. I Have extracted the pixel values of the bands with that of the training polygons. In all I had 226 observations and the 8 bands as the response variables.
I tried to split it into 70% for training set and 30% for as testing set sing the codes below; #setting training and testing samples set.seed(999) id <- sample(2, nrow(dfTrainshape), prob = C(0.7, 0.3), replace = TRUE) dfTrainshape_train <- dfTrainshape[id==1,] dfTrainshape_test <- dfTrainshape[id==2,] I had the error below; set.seed(999) > id <- sample(2, nrow(dfTrainshape), prob = C(0.7, 0.3), replace = TRUE) Error in C(0.7, 0.3) : object not interpretable as a factor > dfTrainshape_train <- dfTrainshape[id==1,] Error in `[.data.frame`(dfTrainshape, id == 1, ) : object 'id' not found I will be glad to have some advice and probable some code to assist me. Secondly, Please I also want to create a separate testing polygons for the validation in ArcMap. I want to know how I will be able to use the 226 observations of the earlier set of polygons for the training and the new polygons for validation. I will be glad to have some codes which I can change to suite what I want to do. Hope to hear from you. Best regards, Enoch -- *Enoch Gyamfi - Ampadu* *Geography & Environmental Sciences* *College of Agriculture, Engineering & Science* *University of KwaZulu-Natal, Westville Campus* *Private Bag X54001* *Durban, South Africa **– 4000**.* *Phone: +27 835 828255* *email: egamp...@gmail.com <egamp...@gmail.com>* *skype: enoch.ampadu* *The highest evidence of nobility is self-control*. *A simple act of kindness creates an endless ripple*. [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo