thengl

library(mlr)

## Synthetic data ----
set.seed(200)
n = 100
x <- 1:n
y <- x + rnorm(n = 50, mean = 15, sd = 15)
dat <- data.frame(x,y)
## newdata:
newdata <- data.frame(

thengl

## Synthetic data ----
set.seed(200)
n = 100
x <- 1:n
y <- x + rnorm(n = 50, mean = 15, sd = 15)

## Synthetic linear model ----
m0 <- lm(y ~ x)
summary(m0)
# Residuals:

thengl

## original script: https://gist.github.com/dylanbeaudette/b386f0008133167f518960a113283a0d#file-help-this-poor-rf-model-r
## discussion: https://twitter.com/DylanBeaudette/status/1410666900581851138
## by: tom.hengl@opengeohub.org

library(rpart)
library(rms)
library(ranger)
library(kernlab)
library(mboost)
library(landmap)

thengl

## orignal script: https://gist.github.com/dylanbeaudette/b386f0008133167f518960a113283a0d#file-help-this-poor-rf-model-r
## discussion: https://twitter.com/DylanBeaudette/status/1410666900581851138

library(randomForest)
library(ranger)
library(rpart)
library(rms)
library(mlr)
library(forestError)
rmse <- function(a, b) {