| # Setting up random matrix | |
| set.seed(11111) | |
| x <- data.frame(a = rnorm(n = 15) * 5, | |
| b = rnorm(n = 15) * 3 + 1, | |
| c = rnorm(n = 15) * 2 + 2) | |
| # Setting up the (perfect) linear relationship | |
| y <- 2 + (x[, 1] * 2) + (x[, 2] * 3) + (x[, 3] * 4) + (x[, 3] ^ 2) + (x[, 1] * x[, 2]) | |
| # Setting up polynomial features |
| # Setting up random matrix | |
| set.seed(11111) | |
| x <- data.frame(a = rnorm(n = 15) * 5, | |
| b = rnorm(n = 15) * 3 + 1, | |
| c = rnorm(n = 15) * 2 + 2) | |
| # Setting up an imperfect relationship (non-linear problem) | |
| y <- as.integer((2 + (x[, 1] * 2) + (x[, 2] * 3) + (x[, 3] * 4) + (x[, 3] ^ 2) + (x[, 1] * x[, 2])) > 20) | |
| # Setting up polynomial features |
| # Setting up random matrix | |
| set.seed(11111) | |
| x <- data.frame(a = rnorm(n = 100) * 5, | |
| b = rnorm(n = 100) * 3 + 1, | |
| c = rnorm(n = 100) * 2 + 2) | |
| # Setting up an imperfect relationship (non-linear problem) with +1 or -1 for classes | |
| y <- 2 * as.integer((2 + (x[, 1] * 2) + (x[, 2] * 3) + (x[, 3] * 4) + (x[, 3] ^ 2) + (x[, 1] * x[, 2])) > 20) - 1 | |
| # Setting up polynomial features |
| library(plotly) | |
| library(ggplot2) | |
| plot1 <- function(data, title) { | |
| ggplot(data = data, aes(x = Threading, y = Score, fill = Score)) + geom_bar(stat = "identity", color = "black") + geom_label(aes(label = Score, y = mean(Score) * 0.05 + Score, fill = Score), position = "identity", color = "white", fontface = "bold") + scale_fill_gradientn(colours = c("#ff9999", "#33cc33")) + labs(title = title, x = "Threading Mode", y = "Cinebench R15 Score", fill = "Score") + theme_bw() | |
| } | |
| plot2 <- function(data, title) { | |
| ggplot(data = data, aes(x = Threading, y = ScoreScale, fill = ScoreScale)) + geom_bar(stat = "identity", color = "black") + geom_label(aes(label = round(ScoreScale, digits = 2), y = mean(ScoreScale) * 0.05 + ScoreScale, fill = ScoreScale), position = "identity", color = "white", fontface = "bold") + scale_fill_gradientn(colours = c("#ff9999", "#33cc33")) + labs(title = title, x = "Threading Mode", y = "Scaled Cinebench R15 Score (GHz)", fill = "Scale") + theme_bw() | |
| } |
| packages <- c("abind", "acepack", "actuar", "ActuDistns", "ada", | |
| "adabag", "addinplots", "ade4", | |
| "ade4TkGUI", "adegraphics", "adehabitatLT", "adehabitatMA", "ADGofTest", | |
| "AER", "AGD", "agricolae", "AICcmodavg", "akima", "alabama", | |
| "AlgDesign", "alphahull", "alr3", "alr4", "amap", "Amelia", "anchors", | |
| "animation", "aod", "aods3", "ape", "aplpack", | |
| "argparse", "arm", "arules", "arulesViz", "ascii", | |
| "assertthat", "AUC", "BaBooN", "backports", "barcode", "bartMachine", | |
| "bartMachineJARs", "base64", "base64enc", "BatchJobs", | |
| "BayesFactor", "bayesplot", "BayesX", "BayesXsrc", "BB", "BBmisc", |
| # List all possible power config GUIDs in Windows | |
| # Run: this-script.ps1 | Out-File powercfg.ps1 | |
| # Then edit and run powercfg.ps1 | |
| # (c) Pekka "raspi" Järvinen 2017 | |
| $powerSettingTable = Get-WmiObject -Namespace root\cimv2\power -Class Win32_PowerSetting | |
| $powerSettingInSubgroubTable = Get-WmiObject -Namespace root\cimv2\power -Class Win32_PowerSettingInSubgroup | |
| Get-WmiObject -Namespace root\cimv2\power -Class Win32_PowerSettingCapabilities | ForEach-Object { | |
| $tmp = $_.ManagedElement |
| # library(data.table) | |
| # N=2e9; K=100 | |
| # set.seed(1) | |
| # DT <- data.table( | |
| # id1 = sample(sprintf("id%03d",1:K), N, TRUE), # large groups (char) | |
| # id2 = sample(sprintf("id%03d",1:K), N, TRUE), # large groups (char) | |
| # id3 = sample(sprintf("id%010d",1:(N/K)), N, TRUE), # small groups (char) | |
| # id4 = sample(K, N, TRUE), # large groups (int) | |
| # id5 = sample(K, N, TRUE), # large groups (int) | |
| # id6 = sample(N/K, N, TRUE), # small groups (int) |
| library(Rcpp) | |
| Sys.setenv(PKG_CXXFLAGS = "-fopenmp -std=c++11") | |
| cppFunction(code = '#include <Rcpp.h> | |
| #include <omp.h> | |
| Rcpp::NumericVector streamer(Rcpp::NumericVector threads, int triad_size = 2147483647, int repeats = 10, int repeats_alloc = 3, bool simd = false) { | |
| int i; |
Step 1: download cplexAPI : Step 2: edit src/Makevars.win like the following, make sure cplex1280 is equal to your version you must change to the corresponding number you can find in C:/Program Files/IBM/ILOG/CPLEX_Studio128/cplex/bin/x64_win64:
PKG_CPPFLAGS=-g -D_R_=1 -DUSE_R=1 -I"C:/Program Files/IBM/ILOG/CPLEX_Studio128/cplex/include"
PKG_LIBS=-L"C:/Program Files/IBM/ILOG/CPLEX_Studio128/cplex/bin/x64_win64" -lm -lcplex1280
Step 3: in a R console, on the right folder:
| library(xgboost) | |
| set.seed(1) | |
| N <- 10000000 | |
| p <- 100 | |
| pp <- 25 | |
| X <- matrix(runif(N * p), ncol = p) | |
| betas <- 2 * runif(pp) - 1 | |
| sel <- sort(sample(p, pp)) | |
| m <- X[, sel] %*% betas - 1 + rnorm(N) |