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title: My last R posts: How conformalization helps weak models,...
description: A roundup of recent R blog posts covering three topics: using scikit-learn models in R via the tisthemachinelearner package (with support for split conformal...
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og:description: A roundup of recent R blog posts covering three topics: using scikit-learn models in R via the tisthemachinelearner package (with support for split conformal...
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# My last R posts: How conformalization helps weak models, fast conformal prediction with jackknife+ (and no refitting), and sklearn in R

**[R-bloggers](https://daily.dev/sources/rbloggers)** · 2 min read · 0 upvotes · 0 comments

## Summary

A roundup of recent R blog posts covering three topics: using scikit-learn models in R via the tisthemachinelearner package (with support for split conformal prediction, surrogate methods, and bootstrap), how conformalization improves weak predictive models using split conformal prediction, and fast jackknife+ conformal prediction intervals for linear-algebra-based ML models (OLS, Ridge, RVFL, Kernel Ridge, etc.) without any model refitting.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.r-bloggers.com/2026/07/my-last-r-posts-how-conformalization-helps-weak-models-fast-conformal-prediction-with-jackknife-and-no-refitting-and-sklearn-in-r>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#r](https://daily.dev/tags/r), [#scikit](https://daily.dev/tags/scikit)

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