jakob-r

# Author: Jakob Richter (https://gist.github.com/jakob-r)
# colfuncMiddle does the same as colfunc but gives respect to middle point.
# usage: x : numeric() 
#        colfunc: function generated by colorRampPalette()
#        zeropoint: numeric(1)

colfuncMiddle = function(x, colfunc, n, zeropoint=0){
  stopifnot(is.numeric(x) | is.factor(x))
  if(!missing(n)){
    stopifnot(length(n)==1)

jakob-r

library(checkmate)
library(mlr)

makePersp3DLayer = function(opt.path.dt, par.set = NULL, learner, y = "y", x = NULL, resolution = 100, nrow.limit = 400) {
  x = coalesce(x, getParamIds(par.set))
  assertCharacter(x, len = 2)
  data = opt.path.dt[, c(x,y), with=FALSE]
  if (nrow(opt.path.dt) > nrow.limit) {
    data = data[sample(nrow(data), size = nrow.limit),]
  }

jakob-r

waitAndSubmitExpired = function(reg, resources, wait = 30, ...) {
  done.ids = findDone(reg)
  error.ids = findErrors(reg)
  expired.ids = findExpired(reg)
  submitted.ids = findSubmitted(reg)
  restarted.ids = numeric()
  
  while (!all(submitted.ids %in% c(done.ids, error.ids))) {
    if (length(expired.ids) > 0)
      submitJobs(reg, expired.ids, resources = resources, ...)

jakob-r

surrogate.learner = makeLearner("regr.randomForest", predict.type = "se")

myTrafo = function(data, target, category, na.val) {
  catf("run mytrafon on data with")
  data.notarget = data[, colnames(data) != target, drop = FALSE]
  data = cbind(dcast(data.notarget, as.formula(paste0("seq_along(", category, ")~",category)), fill = na.val, value.var = "x", drop = FALSE)[, -1, drop = FALSE], data[,colnames(data) %in% c(category, target), drop = FALSE])
  return(data)
}
wrpTrain = function(data, target, args) {
  data = myTrafo(data = data, target = target, category = args$category, na.val = args$na.val)

jakob-r

library(mlrMBO)
library(data.table)
library(ggplot2)
configureMlr(on.par.without.desc = "warn")
set.seed(1)
# Define objective function
fn = makeRosenbrockFunction(5)

# define mbo control object
ctrl = makeMBOControl(propose.points = 4, store.model.at = 0:20)

jakob-r

library(mlrMBO)
library(stringi)
library(jsonlite)

# read command line args (in a not very safe way)
# Script can be called like that:
# Rscript runMBO.R iters=20 time=10 seed=1
args = commandArgs(TRUE)
# defaults:
iters = 50

jakob-r

n = 5
x = runif(1000 * n)
mat = matrix(x, ncol = n)
mat2 = apply(mat, 1, function(x) {
  ox = order(x)
  rox = match(x, x[ox])
  dx = diff(c(0,x[ox]))
  dx[rox]
})
mat2 = t(mat2)

jakob-r

Keybase proof

I hereby claim:

• I am jakob-r on github.
• I am jakobr (https://keybase.io/jakobr) on keybase.
• I have a public key ASA0uw1eePgkoFeZK9YbYrkjVOld8XKdql-qIFLAALvwWwo

To claim this, I am signing this object:

jakob-r

#' @title Build ensemble of multiple learners with sampled hyperparameters.
#'
#' @description
#' Define a learner and define which hyperparameters should get sampled.
#' The ensemble will be build of multiple learners, each with different random hyperparamters.
#' The predictions for mean and se will be averaged.
#'
#' @template arg_learner
#' @param samplers (`list`)\cr
#'   A named list of functions that create the random samples:

jakob-r

\documentclass{beamer}

\usepackage[absolute,overlay]{textpos}
\usepackage{import} 
\setbeamercolor{background canvas}{bg=gray}

\setkeys{Gin}{width=\linewidth} % default of includegraphics width

\begin{document}