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🔥 Top post: 📦 My new R package {spatialData} is on CRAN! 🎉 Ecological datase · 24 likes + reposts
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4/5 tidymodels integration
The new function step_collinear() lets you add multicollinearity filtering directly into your {recipes} pipelines.
This integration omits target-encoding, as it doesn’t fit well with how recipes work.
3/5 Enriched output
The output of collinear() now takes you from raw data to model-ready output::
- Filtered data frame
- Ranking of predictors resulting from preference_order()
- Names of the selected predictors
- Model formulas to kicks…
2/5 Adaptive thresholds
By default, {collinear} analyzes the data's correlation structure to configure multicollinearity thresholds automatically.
The figure shows how this approach keeps output VIF bounded within reasonable limits across…
{collinear} 3.0 is now on CRAN!
This #rstats package automates multicollinearity management to improve model robustness and interpretability.
You can learn more at https://blasbenito.github.io/collinear/, but here's a summary of the most e…
#Rstats package {distantia} version 2.0.1, with a few bugfixes, is now on CRAN: https://blasbenito.github.io/distantia/news/index.html#version-201
I wrote a #rstats tutorial on how to build a dynamic time warping library (not a package) from scratch, with no dependencies or abstractions, and fully focused on code readability.
"Coding a Minimalistic Dynamic Time Warping Library with R…
Following the release of {distantia} 2.0, I wrote the blog post "A Gentle Intro to Dynamic Time Warping" with a conceptual description of the method (no code at all) and a summary of some interesting real-world applications: https://www.bl…
The package includes a complete toolset to manage time series, described here: https://blasbenito.github.io/distantia/articles/time_series_lists.html, and even some tools to help map dissimilarity between time series, as shown in this arti…
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