Customer and Marketing Analysis in R

Clean the Environment # Clear environment of variables and functions rm(list = ls(all = TRUE)) # Clear environmet of packages if(is.null(sessionInfo()$otherPkgs) == FALSE)lapply(paste("package:", names(sessionInfo()$otherPkgs), sep=""), detach, character.only = TRUE, unload = TRUE) Load Libraries library(tidyverse) library(dplyr) # joins library(RODBC) # connect to SQL Server library(janitor) # pretty cross-tabs library(kableExtra) # pretty html tables library(formattable) library(gridExtra) … Continue reading Customer and Marketing Analysis in R

R Package for Data Scientist

library(tidyverse) library(sqldf) library(tidyverse) library(dplyr) # joins library(janitor) # pretty cross-tabs library(kableExtra) # pretty html tables library(formattable) library(gridExtra) library(scales) library(pastecs) library(GGally) library(ChannelAttribution) library(markovchain)

Random Forest

With excellent performance on all eight metrics, calibrated boosted trees were the best learning algorithm overall. Random forests are close second, followed by uncalibrated bagged trees, calibrated SVMs, and un- calibrated neural nets. -- Rich Caruana, Alexandru Niculescu-Mizil link: https://www.cs.cornell.edu/~caruana/ctp/ct.papers/caruana.icml06.pdf Definition Decision Tree is a schematic, tree-shaped diagram used to determine a course of action … Continue reading Random Forest