Presubmission: “We encourage you to submit.”
1-month editorial review.
Final decision: “No capacity for unsolicited Comments.”

Same journal, two different editors.
Zero feedback on content.
A month lost to an avoidable structural contradiction in academic publishing.

Introducing fastml for R! 🚀
🛡️ Guarded Resampling: Prevents data leakage by design.
🌲 Native Survival: Custom XGBoost AFT & Piecewise engines that outperform baselines.
🔒 Security Sandbox: Safe execution for user-defined recipes.
Build robust models in one line of code. #rstats #automl #datascience

🚀 Tired of writing 200 lines of code just to train and tune models in R? Meet fastml.

fastml takes data from raw form to tuned models with explainability in a single function call.

Here is a thread on solving Customer Churn in <10 lines of code. 🧵👇
#rstats #datascience
github.com/selcukorkmaz...

1/8 Building a machine learning model that truly generalizes depends on a few simple but critical rules. If these are violated, the model can look great on paper but collapse in the real world.

fastml brings a unified machine-learning workflow to R.

• Automated model training and tuning
• Leakage-safe resampling by design
• Built-in survival analysis
• Integrated explainability

A streamlined way to build reliable models with minimal code.

#rstats #machinelearning #datascience

PubChemR gives fast, reproducible access to PubChem data including CIDs, SIDs, assays, structures and annotations directly in R, streamlining chemical-data workflows for analysis and ML.

#RStats #Cheminformatics #Bioinformatics cran.r-project.org/web/packages...

PubChemR gives fast, reproducible access to PubChem data including CIDs, SIDs, assays, structures and annotations directly in R, streamlining chemical-data workflows for analysis and ML.

#RStats #Cheminformatics #Bioinformatics cran.r-project.org/web/packages...

fastml is an R package that builds leak-free, fully reproducible machine-learning pipelines with minimal code. It automates splitting, preprocessing, tuning, and evaluation while enforcing strict anti-leakage rules and providing integrated explainability tools.
#MachineLearning #Rstats #DataScience

fastml is an R package that builds leak-free, fully reproducible machine-learning pipelines with minimal code. It automates splitting, preprocessing, tuning, and evaluation while enforcing strict anti-leakage rules and providing integrated explainability tools.
#MachineLearning #Rstats #DataScience

🚀 Stop writing hundreds of lines of boilerplate code for Machine Learning in R.

If you’ve used tidymodels or mlr3, you know the workflow can become verbose: recipes, encoders, CV folds, tuning grids, leakage risks…

fastml aims to solve this.

cran.r-project.org/web/packages...