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R packages for data validation. Use for validating data quality and constraints.
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Based on SOC occupation classification
R language data analysis and visualization skill. Use when user asks to (1) run R scripts or code, (2) install/update R packages, (3) perform data analysis with R, (4) create visualizations with ggplot2/plotly, (5) statistical analysis, (6) data manipulation with tidyverse/dplyr/data.table. Triggers on keywords like "R语言", "R脚本", "ggplot", "tidyverse", "数据分析", "可视化".
R DALEX package for model explanations. Use for explaining complex machine learning models.
R iml package for interpretable ML. Use for model-agnostic interpretability methods.
R lime package for local explanations. Use for explaining individual predictions with local interpretable models.
R packages for ML interpretability. Use for explaining and interpreting machine learning models.
R vip package for variable importance. Use for computing and visualizing variable importance scores.
| name | r-data-validation |
| description | R packages for data validation. Use for validating data quality and constraints. |
Validate data quality and constraints.
| Package | Purpose |
|---|---|
| validate | Rule-based validation |
| assertr | Assertion pipelines |
| pointblank | Data quality reporting |
