Model-Agnostic Response Curves for Fitted Models
Overview
Create model-agnostic response-curve diagnostics for fitted prediction models. Supports profile curves, partial dependence, individual conditional expectation, and accumulated local effects; univariate curves, bivariate surfaces, ensemble summaries across multiple models, ALE-based interaction ranking, and optional raster-linked exploration with 'terra' and 'shiny'. Static displays are returned as 'ggplot2' plots. For more details on the methods see Molnar (2025) https://christophm.github.io/interpretable-ml-book/.
New features
- Added
interactions(), which ranks numeric predictor pairs by the count-weighted magnitude of their centred second-order ALE surfaces. - Added
top_ntobivariate()formethod = "ale"so the plotting interface can rank all eligible pairs withinteractions()and display only the strongest interaction surfaces.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK8 OK2026-05-12
Documentation
- Help pages
- 6 (1 internal)includes a package overview page
- Examples that run
- 100%5 run in a plain check (2 of them under a condition)
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 100%
Downloads
Repository
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Dependencies
Code & Tests
People & History
- 0.4.0Latest2026-05-11 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-05-11
- Total releases
- 1 / 1 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 5.4 MB
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