01-overview.Rmd

# Overview

## Package installation

The following packages are required to run the code in this workshop:

```{r setup}

# Install packages 
if (!require("pacman")) install.packages("pacman")

install.packages("tidyverse")

pacman::p_load(# Tidymodels framework 
               tidymodels,
               # Tidyverse packages including dplyr and ggplot2 
               tidyverse,
               # Algorithms
               glmnet, ranger, rpart, xgboost, pvclust, mclust, 
               # Visualization
               rpart.plot, vip, ape, corrr, GGally,
               # Machine learning frameworks
               caret, SuperLearner,
               # R utility packages
               remotes, here, glue, patchwork, doParallel,
               # Import/export of any filetype.
               rio,
               # Misc
               pROC, bookdown)
  
# Install packages not on CRAN or with old version on CRAN.
remotes::install_github("ck37/ck37r")

# Hide the many messages and possible warnings from loading all these packages.
suppressMessages(suppressWarnings({  
  library(ape)          # Cluster visualizations
  library(caret)        # createDataPartition creates a stratified random split 
  library(ck37r)        # impute_missing_values, standardize, SuperLearner helpers
  library(glmnet)       # Lasso 
  library(mclust)       # Model-based clustering
  library(PCAmixdata)   # PCA
  library(pROC)         # Compute and plot AUC 
  library(pvclust)      # Dendrograms with p-values
  library(ranger)       # Random forest algorithm
  library(remotes)      # Allows installing packages from github
  library(rio)          # Import/export for any filetype.
  library(rpart)        # Decision tree algorithm
  library(rpart.plot)   # Decision tree plotting
  library(SuperLearner) # Ensemble methods
  library(xgboost)      # Boosting method
  library(vip)          # Variable importance plots
}))

```