Man pages for midr
Learning from Black-Box Models by Maximum Interpretation Decomposition
| color.theme | Color Themes for Graphics |
| color.theme.info | Retrieve Color Theme Information |
| factor.encoder | Encoder for Qualitative Variables |
| get.yhat | Wrapper Prediction Function |
| ggmid | Plot MID Component Functions with ggplot2 |
| ggmid.mid.breakdown | Plot MID Breakdowns with ggplot2 |
| ggmid.mid.conditional | Plot MID Conditional Expectations with ggplot2 |
| ggmid.mid.importance | Plot MID Importance with ggplot2 |
| interpret | Fit MID Models |
| mid.breakdown | Calculate MID Breakdowns |
| mid.conditional | Calculate MID Conditional Expectations |
| mid.effect | Evaluate Single MID Component Functions |
| mid.importance | Calculate MID Importance |
| mid.plots | Plot Multiple MID Component Functions |
| midr-package | midr: Learning from Black-Box Models by Maximum... |
| mid.terms | Extract Terms from MID Models |
| numeric.encoder | Encoder for Quantitative Variables |
| plot.mid | Plot MID Component Functions |
| plot.mid.breakdown | Plot MID Breakdowns |
| plot.mid.conditional | Plot MID Conditional Expectations |
| plot.mid.importance | Plot MID Importance |
| predict.mid | Predict Method for fitted MID Models |
| print.mid | Print MID Models |
| scale_color_theme | Color Theme Scales for ggplot2 Graphics |
| set.color.theme | Register Color Themes |
| shapviz.mid | Calculate MID-Derived Shapley Values |
| summary.mid | Summarize MID Models |
| theme_midr | Default Plotting Themes |
| weighted.loss | Weighted Loss Function |
| weighted.quantile | Weighted Sample Quantile |
| weighted.tabulate | Weighted Tabulation for Vectors |
