README.Rmd

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output: github_document
---

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knitr::opts_chunk$set(
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# `RFCLUST`

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`RFCLUST` performs Random Forests of Divisive Monothetic ([`divclust`](https://github.com/chavent/divclust)) Trees for Unsupervised Clustering.

## Installation

You can install the development version of RFCLUST from [GitHub](https://github.com/). 

`RFCLUST`depends on a custopmized implementation of the [`divclust`](https://github.com/chavent/divclust) package, that must first be installed with the following:

```{r, eval=FALSE}
# install.packages("remotes")
remotes::install_github("Alar0g/divclust")
```

Then, `RFCLUST` can be installed with:
```{r, eval=FALSE}
remotes::install_github("Alar0g/RFCLUST")
```

## Example

```{r}
library(RFCLUST)
library(palmerpenguins)
mypeng <- as.data.frame(penguins)
mypeng$year <- factor(as.character(mypeng$year),
                         levels=c("2007", "2008", "2009"),
                         ordered=TRUE)

forest_clust <- rfclust(na.omit(mypeng[mypeng$sex=="male", -c(1, 7)]), ntrees = 50, ncores = 1)

resume <- summary(forest_clust)
plot(resume)
```