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我的 R 语言数据分析笔记（待修改）

Make awesome display tables using Python

SHAP Plots in R

Online version of Bischl, B., Sonabend, R., Kotthoff, L., & Lang, M. (Eds.). (2024). "Applied Machine Learning Using mlr3 in R". CRC Press.

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📦 BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.

Repository for the OpenMx Structural Equation Modeling package

🛠 BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.

An R wrapper of SHAP python library

Fast approximate Shapley values in R

Estimate Permutation p-Values for Random Forest Importance Metrics

💪 Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)

🔮 Easy access to model information for various model objects

moDel Agnostic Language for Exploration and eXplanation

DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.

Generalized Random Forests

Triplot: Instance- and data-level explanations for the groups of correlated features.

Materials for teaching R and Stan

An R package for the Quantitative Analysis of Textual Data

sjPlot - Data Visualization for Statistics in Social Science

Mixed-effects models in R using S4 classes and methods with RcppEigen

Regression models and utilities for repeated measures and panel data

mlr3: Machine Learning in R - next generation

Dot-and-Whisker Plots of Regression Results

Beautiful and customizable model summaries in R.

📈 Estimate effects, contrasts and means based on statistical models