#########################################################################################
# Copyright (c) 2016. All rights reserved. See the file LICENSE for
# license terms.
#########################################################################################
# File: LE2_ScoringModel.R
# Proj: R Workshop
# Desc: R - Beyond the Basics,
# Lecture Part 2 (Project)
# Auth: Andrea Bublitz and Claudia Wenzel
# Date: 2017/02/06
#########################################################################################
#' RFMfunction
#' Calculate a weighted RMF score, this is a Description
#
#Arguments
#' @param data - a data table
#' @param weight_recency - weight of recency
#' @param weiht_frequency - weight of frequency
#
#
#' @details mmmmmmmmmmm
#' @return Returns a data.table containing ... xy ...
#' score this is the second line. thank you for smoking.
#' @export
#Set working directory ####
#setwd("~/Dropbox/R - Beyond the basics/Lectures/data")
#Make sure to set your working directory correctly!
#Install (if necessary) and load the following packages. ####
# 5. The RFM function ####
RFMfunction <- function(data, weight_recency=1, weight_frequency=1, weight_monetary=1){
library(data.table)
library(lubridate)
library(Hmisc)
# Ensure that the weights add up to one
weight_recency2 <- weight_recency/sum(weight_recency, weight_frequency, weight_monetary)
weight_frequency2 <- weight_frequency/sum(weight_recency, weight_frequency, weight_monetary)
weight_monetary2 <- weight_monetary/sum(weight_recency, weight_frequency, weight_monetary)
# RFM measures
max.Date <- max(data$TransDate)
temp <- data[,list(
recency = as.numeric(max.Date - max(TransDate)),
frequency = .N,
monetary = sum(PurchAmount)/.N),
by="Customer"
]
# RFM scores
temp <- temp[,list(Customer,
recency = as.numeric(cut2(-recency, g=3)),
frequency = as.numeric(cut2(frequency, g=3)),
monetary = as.numeric(cut2(monetary, g=3)))]
# Overall RFM score
temp[,finalscore:=weight_recency2*recency+weight_frequency2*frequency+weight_monetary2*monetary]
# RFM group
temp[,group:=round(finalscore)]
# Return final table
return(temp)
}
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