DexGroves

library("data.table")
library("xgboost")
library("Matrix")


generate_data <- function(N) {
  data.table(
    response = as.numeric(runif(N) > 0.8),
    float1   = rnorm(N, 3, 3))
}

DexGroves

library("data.table")


fread("a,b\n1,T\n1,T\n1,T\n1,T\n1,T\n2,C\n")
#    a b
# 1: 1 1
# 2: 1 1
# 3: 1 1
# 4: 1 1
# 5: 1 1

DexGroves

strip_glm <- function(cm) {
  cm$y = c()
  cm$model = c()
  
  cm$residuals = c()
  cm$fitted.values = c()
  cm$effects = c()
  cm$qr$qr = c()  
  cm$linear.predictors = c()
  cm$weights = c()

DexGroves

strip_glm <- function(cm) {
  cm$y = c()
  cm$model = c()
  
  cm$residuals = c()
  cm$fitted.values = c()
  cm$effects = c()
  cm$qr$qr = c()  
  cm$linear.predictors = c()
  cm$weights = c()

DexGroves

import itertools
import numpy as np 
from collections import Counter


def person_says_no(possibilities):
    uniqueness = Counter([d.values()[0] 
                         for d in possibilities]).items()
    impossibilities = [x for (x, count) in uniqueness if count == 1]

DexGroves

library("mlbench")
library("gbm")
library("ggplot2")


get_spiral_df <- function(N, cycles, sd) {
  spiral_data <- mlbench.spirals(N, cycles, sd)
  data.frame(x = spiral_data$x[, 1],
             y = spiral_data$x[, 2],
             class = as.numeric(spiral_data$classes) - 1)

DexGroves

sudo apt-get update
sudo apt-get install -y build-essential git libatlas-base-dev libopencv-dev

git clone --recursive https://github.com/dmlc/mxnet
cd mxnet; 

cp make/config.mk .

#add CUDA options
echo "USE_CUDA=1" >>config.mk

DexGroves

library("mlbench")
library("ggplot2")
library("mxnet")


plot_mxmodel <- function(model, data) {
  x <- seq(from = min(data), to = max(data), length.out = 500)
  d2 <- as.matrix(expand.grid(x, x))

  mx_pred <- predict(model, d2)

DexGroves

# Instantiate local CRAN
localCRAN <- path.expand("QRAN")
dir.create(localCRAN)

contribDir <- file.path(localCRAN, "src", "contrib")
dir.create(contribDir, recursive = TRUE)

rVersion <- paste(unlist(getRversion())[1:2], collapse = ".")

binPaths <- list(

DexGroves

generate_fks <- function(N) {
  fki <- log(N + 1)
  fks <- c(fki)

  for (i in seq(N)) {
    fki <- log(exp(fki) - fki)
    fks <- c(fks, fki)
  }

  fks