https://github.com/mattansb/machine-learning-for-psychologists

Lesson files used in the Machine Learning foR Psychologists
https://github.com/mattansb/machine-learning-for-psychologists

bgu-university caret psychologists rstats statistics tau-university teaching-materials tidymodels

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Lesson files used in the Machine Learning foR Psychologists

• Host: GitHub
• URL: https://github.com/mattansb/machine-learning-for-psychologists
• Owner: mattansb
• License: other
• Created: 2023-06-03T17:48:40.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-09-03T06:52:12.000Z (5 months ago)
• Last Synced: 2024-10-11T18:23:17.801Z (4 months ago)
• Topics: bgu-university, caret, psychologists, rstats, statistics, tau-university, teaching-materials, tidymodels
• Language: R
• Homepage:
• Size: 181 KB
• Stars: 4
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE

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README

        
---

output: github_document

---

```{r setup, include=FALSE}

library(knitr)

opts_chunk$set(echo = TRUE)

```

# Machine Learning foR Psychologists

[![](https://img.shields.io/badge/Open%20Educational%20Resources-Compatable-brightgreen)](https://creativecommons.org/about/program-areas/education-oer/)

[![](https://img.shields.io/badge/CC-BY--NC%204.0-lightgray)](http://creativecommons.org/licenses/by-nc/4.0/)  

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

*Last updated `r Sys.Date()`.*

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)")

```

Package Versions

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`