search for: outlyingness_all

...ngness <- rep(NaN,tries) for (o_number in 1:tries){ features <- matrix(rnorm(n*dimension,0,1),n,dimension) #Generate features, n uncorrelated normally distributed points outlier.rf <- randomForest(features, ntree=100, proximity=TRUE) #Compute Random Forest including the proximity matrix outlyingness_all <- apply(outlier.rf$proximity,2,mean) #Compute the mean proximity for each of the n points better <- sum(outlyingness_all[1]<outlyingness_all) #Compute the rank of a certain point according to the outlyingness outlyingness[o_number] <- 1+better } outlyingness P...