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simple_roc <- function(labels, scores){
labels <- labels[order(scores, decreasing=TRUE)]
data.frame(TPR=cumsum(labels)/sum(labels), FPR=cumsum(!labels)/sum(!labels), labels)
}
# Import relevant packages
library(dplyr)
library(tidyverse)
library(arulesSequences)
#Import standard transaction data
transactions = read.csv("transactions.csv")
# Start time of data to be considered
start_month <- "2015-07-01"
@revodavid
revodavid / CRAN_pkg_history.R
Last active May 1, 2021 12:58 — forked from andrie/CRAN_pkg_history.R
Scrapes CRAN for historical number of packages per release
# Scrapes CRAN archives to determine the number of packages per release
# Create a list of pages to scrape, including both archive and current
extract_url <- function() {
url <- list(
archive = "https://cran-archive.r-project.org/bin/windows/contrib/",
active = "https://cran.r-project.org/bin/windows/contrib/"
)
get_urls <- function(url) {
---
title: "Outliers are a matter of opinion?"
author: "Antony Unwin"
date: ' '
output: html_document
---
```{r include=FALSE}
library(ggplot2)
library(ggthemes)
library(OutliersO3)
@revodavid
revodavid / slide-code.R
Created February 3, 2020 22:21
R code for slides in "Machine Learning Operations for R"
#### Code from slides
## This code is excerpted from experiments-with-R.Rmd,
## edited and reformatted for use on slides
## SLIDE: Prepare Data
library(azuremlsdk)
ws <- load_workspace_from_config()
# Get frequent sequences and corresponding support values
s1 <- cspade(trans_matrix, parameter = list(support = 0.3), control = list(verbose = TRUE))
s1.df <- as(s1, "data.frame")
summary(s1)
library(AzureRMR)
library(AzureGraph)
library(AzureStor)
# set your Azure organization and subscription details here
tenant <- "mytenant"
sub_id <- "12345678-aaaa-bbbb-cccc-0123456789ab"
# create a Graph client
gr <- AzureGraph::create_graph_login(tenant)
## get n colors at once
random.colors <- function(n) {
hexbot <- GET(endpoint, query=list(count=n))
unlist(content(hexbot)$colors)
}
ncol <- 5
barplot(rep(1,ncol),col=random.colors(ncol), axes=FALSE)
## get n colors with locations
random.points <- function(n,width=100,height=100) {
hexbot <- GET(endpoint, query=list(count=n, width=width, height=height))
data <- matrix(unlist(content(hexbot)$colors),ncol=3,byrow=TRUE)
cols <- data[,1]
x <- as.numeric(data[,2])
y <- as.numeric(data[,3])
data.frame(cols, x, y)
}
## get a single color, and display on screen
random.color <- function() {
hexbot <- GET(endpoint)
content(hexbot)$colors[[1]]$value
}
rcol <- random.color()
barplot(1, col=rcol, main=rcol, axes=FALSE)