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lorismichel / quantregForest

R package - Quantile Regression Forests, a tree-based ensemble method for estimation of conditional quantiles (Meinshausen, 2006).
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MSE with parallel computation #10

Open aparrar1 opened 5 years ago

aparrar1 commented 5 years ago

I am using quantregForest with parallel computation and I have noticed that the mean squared error values are not getting calculated when using the parallel option. I am not sure why this is happening, looking at the parallelRandomForest code it looks like mse should be part of the output of the function.

Following the example in the documentation:

library("randomForest") library("quantregForest") library("parallel")

data(airquality) set.seed(1) airquality <- airquality[ !apply(is.na(airquality), 1,any), ] n <- nrow(airquality) indextrain <- sample(1:n,round(0.6*n),replace=FALSE) Xtrain <- airquality[ indextrain,2:6] Ytrain <- airquality[ indextrain,1]

qrf <- quantregForest(x=Xtrain, y=Ytrain, keep.inbag = TRUE, importance=TRUE) qrf$mse plot(qrf)

qrf <- quantregForest(x=Xtrain, y=Ytrain, keep.inbag = TRUE, importance=TRUE, nthreads=10) qrf$mse NULL plot(qrf) Error in array(x, c(length(x), 1L), if (!is.null(names(x))) list(names(x), :'data' must be of a vector type, was 'NULL'