Create accountLogin

Recent searches

No recent searches

Search options

Only available when logged in.
livellosegreto.it is one of the many independent Mastodon servers you can use to participate in the fediverse.
Livello Segreto è il social etico che ha rispetto di te e del tuo tempo.

Administered by:

Server stats:

1.2K
active users

livellosegreto.it: AboutProfiles directoryPrivacy policy

Mastodon: AboutGet the appKeyboard shortcutsView source codev4.3.7

#rstats

124 posts106 participants13 posts today
Public
Johann Joets

r-bloggers.com/2025/04/setting
#rstats #crossValidation #modeling

R-bloggers · Setting Up Cross-Validation (caret package) in R: A Step-by-Step Guide | R-bloggersIn this blog, we explored how to set up cross-validation in R using the caret package, a powerful tool for evaluating machine learning models. Here’s a quick recap of what we covered: Introduction to Cross-Validation: Cross-validation is a resampling technique that helps assess model performance and prevent overfitting by testing the model on multiple subsets … Continue reading Setting Up Cross-Validation (caret package) in R: A Step-by-Step GuideSetting Up Cross-Validation (caret package) in R: A Step-by-Step Guide was first posted on April 13, 2025 at 7:08 am.
Public
Johann Joets

r-bloggers.com/2025/04/data-sp
#rstats #sampling

R-bloggers · Data Splitting and Preprocessing (rsample) in R: A Step-by-Step Guide | R-bloggersData preprocessing is a crucial step in any machine learning workflow. It ensures that your data is clean, consistent, and ready for modeling. In this blog post, we’ll walk through the process of splitting and preprocessing data in R, using the rsample package for data splitting and saving the results for future use. Here’s what … Continue reading Data Splitting and Preprocessing (rsample) in R: A Step-by-Step GuideData Splitting and Preprocessing (rsample) in R: A Step-by-Step Guide was first posted on April 13, 2025 at 7:08 am.
Public
Ella Kaye

Yay Palmer Penguins! 🐧 Thanks @scottish for the shout-out for {basepenguins}. In #RStats 4.5.0 penguins data set has some shorter variable names. The {basepenguins} 📦 converts scripts that use {palmerpenguins} to use the native version, taking care of these differences. ellakaye.github.io/basepenguin datasci.social/@scottish/11431

ellakaye.github.ioConvert Files that Use palmerpenguins to Work with datasetsFrom R 4.5.0, the datasets package includes the penguins and penguins_raw data sets popularised in the palmerpenguins package. basepenguins takes files that use the palmerpenguins package and converts them to work with the versions from datasets (R >= 4.5.0). It does this by removing calls to library(palmerpenguins) and making the necessary changes to column names. Additionally, it provides helper functions to define new files paths for saving the output and a directory of example files to experiment with.
Public
agrogan

I’d like to share that my book, Multilevel Thinking: Discovering Variation, Universals, and Particulars in Cross-Cultural Research is available for pre-order at Oxford University Press: global.oup.com/academic/produc

* This book explains multilevel modeling building upon my 15 years of teaching this topic.
* The book contains appendices for estimating multilevel models in #Stata, #Rstats, and #Julialang.

Book cover
Public *
useR! 2025 Conference

🌟 R Dev Day @ useR! 2025: Collaborate, Contribute, Code 🌟
📅 Monday, August 11, 2025
📍 Bostock Library, Duke University, NC, USA
⏰ 2:00 PM - 10:00 PM

Join R enthusiasts for a 1-day event to work on R core development!

Open to useR! 2025 attendees and others. Apply by April 15, 2025 (midnight anywhere on earth).

Participants will be selected to balance experience levels.

👉 Apply here: user2025.r-project.org/additio

user2025.r-project.orgR Dev Day – useR! 2025
#rstats#coding#opensource
Public *
safest_integer

Mapping -diff(y) to linewidth = "light on the upstroke, heavy on the downstroke" = calligraphy

```
library(tidyverse)
library(pracma)
tibble(s = seq(pi, -pi, len = 5000),
x = fresnelS(s), y = fresnelC(s),
wd = c(0, -diff(y))) |>
ggplot() +
geom_path(aes(x=x,y=y, lwd=wd), show.legend=FALSE) +
scale_linewidth_continuous(range=c(.1,2.5)) +
theme_void()
```

#rstats#ggplot2#generativeart
SearchLive feeds
About