README.Rmd

---
output: github_document
---

```{r setup, include=FALSE}
library(knitr)

opts_chunk$set(echo = TRUE)
```

# Machine Learning foR Psychologists

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[![](https://img.shields.io/badge/Language-R-blue)](http://cran.r-project.org/)

<sub>*Last updated `r Sys.Date()`.*</sub>

This Github repo contains all lesson files for *Machine Learning in R*. The goal is to impart students with the basic tools to construct, evaluate and compare various **machine learning models, using [`caret`](https://topepo.github.io/caret/)**. (Materials developed with Yael Bar-Shachar.)

These topics were taught in the graduate-level course ***Machine Learning for Psychologists*** (Psych Dep., Ben-Gurion University of the Negev; Psych Dep., Tel-Aviv University). This course assumes basic competence in R (importing, regression modeling, plotting, etc.), along the lines of [*Practical Applications in R for Psychologists*](https://github.com/mattansb/Practical-Applications-in-R-for-Psychologists).

**Notes:**  

- This repo contains only materials relating to *Practical Applications in R*, and does not contain any theoretical or introductory materials.  
- Please note that some code does not work *on purpose*, to force students to learn to debug.

## Setup

```{r, echo=FALSE}
extract_pkgs <- function(fl) {
  if (length(fl) == 1) {
    txt <- read.delim(fl, header = FALSE)[[1]] |> 
      paste0(collapse = "\n")
    
    pkg_lib <- stringr::str_extract_all(txt, pattern = "(?<=library\\().{1,}(?=\\))")
    
    pkg_req <- stringr::str_extract_all(txt, pattern = "(?<=require\\().{1,}(?=\\))")
    
    pkg_name <- stringr::str_extract_all(txt, pattern = "[a-z|A-Z|0-9]{1,}(?=\\:\\:)")
    
    pkgs <- c(pkg_lib, pkg_req, pkg_name)
    
  } else if (length(fl) > 1) {
    pkgs <- sapply(fl, extract_pkgs)
  }
  
  
  pkgs |>
    unlist(recursive = TRUE) |>
    unique()
}

make_pkg_table <- function(pkgs) {
  pkgs <- pkgs[sapply(pkgs, function(x) length(x) > 0)]
  
  ps <- sapply(pkgs, function(x){
    paste0(
      glue::glue("[`{x}`](https://CRAN.R-project.org/package={x})"),
      collapse = ", "
    )
  })
  
  glue::glue("|[{folder}](/{folder})|{ps}|\n\n",
             folder = names(pkgs)) |> 
    c("|Lesson|Packages|\n|----|----|\n", i2 = _) |> # header
    paste0(collapse = "")
}
```


You will need:

1. A fresh installation of [**`R`**](https://cran.r-project.org/) (preferably version 4.2 or above).
2. [RStudio IDE](https://www.rstudio.com/products/rstudio/download/) (optional, but recommended).
3. The following packages, listed by lesson:

```{r, echo=FALSE, message=FALSE, warning=FALSE}
r_list <- list.files(pattern = ".(R|r)$", recursive = TRUE, full.names = TRUE)
r_list <- r_list[!stringr::str_detect(r_list, pattern = "(SOLUTION|logo)")]
r_list <- r_list[stringr::str_detect(r_list, pattern = "^./[0-9]")]

lesson_names <- stringr::str_extract(r_list, pattern = "(?<=(/)).{1,}(?=(/))")

r_list <- split(r_list, lesson_names)

pkgs <- lapply(r_list, extract_pkgs)

print_pkgs <- make_pkg_table(pkgs)
```

`r print_pkgs`

You can install all the packages used by running:

```{r echo=FALSE, comment = "", warning=FALSE}

pkgs <- pkgs |> 
  unlist(recursive = TRUE) |> 
  unique() |> sort()

cat("# in alphabetical order:")

capture.output(cat("pkgs <-", capture.output(dput(pkgs)), fill = 80)) |>
  styler::style_text()

cat("install.packages(pkgs, dependencies = TRUE)")
```

<details>
<summary><i>Package Versions</i></summary>
The package versions used here:
```{r, echo=FALSE}
packinfo <- installed.packages(fields = c("Package", "Version"))

get_src <- function(pkg) {
  pd <- packageDescription(pkg)
  if (is.null(src <- pd$Repository)) {
    if (!is.null(src <- pd$GithubRepo)) {
      src <- paste0("Github: ",pd$GithubUsername,"/",src)
    } else {
      src <- "Dev"
    }
  }
  return(src)
}

V <- packinfo[pkgs,"Version"]
src <- sapply(pkgs, get_src)
# setNames(paste0(V, " (", src,")"), pkgs)

v_info <- paste0(glue::glue(" - `{pkgs}` {V} (*{src}*)"), collapse = "\n")
```

`r v_info`

</details>