Package: hstats 1.2.2
Michael Mayer
hstats: Interaction Statistics
Fast, model-agnostic implementation of different H-statistics introduced by Jerome H. Friedman and Bogdan E. Popescu (2008) <doi:10.1214/07-AOAS148>. These statistics quantify interaction strength per feature, feature pair, and feature triple. The package supports multi-output predictions and can account for case weights. In addition, several variants of the original statistics are provided. The shape of the interactions can be explored through partial dependence plots or individual conditional expectation plots. 'DALEX' explainers, meta learners ('mlr3', 'tidymodels', 'caret') and most other models work out-of-the-box.
Authors:
hstats_1.2.2.tar.gz
hstats_1.2.2.zip(r-4.5)hstats_1.2.2.zip(r-4.4)hstats_1.2.2.zip(r-4.3)
hstats_1.2.2.tgz(r-4.4-any)hstats_1.2.2.tgz(r-4.3-any)
hstats_1.2.2.tar.gz(r-4.5-noble)hstats_1.2.2.tar.gz(r-4.4-noble)
hstats_1.2.2.tgz(r-4.4-emscripten)hstats_1.2.2.tgz(r-4.3-emscripten)
hstats.pdf |hstats.html✨
hstats/json (API)
NEWS
| # Install 'hstats' in R: |
| install.packages('hstats', repos = c('https://modeloriented.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/modeloriented/hstats/issues
interactioninterpretabilitymachine-learningrstatstatisticsxai
Last updated 2 months agofrom:7553d146f9. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 02 2024 |
| R-4.5-win | OK | Nov 02 2024 |
| R-4.5-linux | OK | Nov 02 2024 |
| R-4.4-win | OK | Nov 02 2024 |
| R-4.4-mac | OK | Nov 02 2024 |
| R-4.3-win | OK | Nov 02 2024 |
| R-4.3-mac | OK | Nov 02 2024 |
Exports:average_lossh2h2_overallh2_pairwiseh2_threewayhstatsicemultivariate_gridpartial_deppd_importanceperm_importanceunivariate_grid
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Subsets "hstats_matrix" Object | [.hstats_matrix |
| Average Loss | average_loss average_loss.default average_loss.explainer average_loss.ranger |
| Dimensions of "hstats_matrix" Object | dim.hstats_matrix |
| Dimnames of "hstats_matrix" Object | dimnames.hstats_matrix |
| Dimnames (Replacement Method) of "hstats_matrix" | dimnames<-.hstats_matrix |
| Total Interaction Strength | h2 h2.default h2.hstats |
| Overall Interaction Strength | h2_overall h2_overall.default h2_overall.hstats |
| Pairwise Interaction Strength | h2_pairwise h2_pairwise.default h2_pairwise.hstats |
| Three-way Interaction Strength | h2_threeway h2_threeway.default h2_threeway.hstats |
| Calculate Interaction Statistics | hstats hstats.default hstats.explainer hstats.ranger |
| Individual Conditional Expectations | ice ice.default ice.explainer ice.ranger |
| Multivariate Grid | multivariate_grid |
| Partial Dependence Plot | partial_dep partial_dep.default partial_dep.explainer partial_dep.ranger |
| PD Bases Importance (Experimental) | pd_importance pd_importance.default pd_importance.hstats |
| Permutation Importance | perm_importance perm_importance.default perm_importance.explainer perm_importance.ranger |
| Plot Method for "hstats" Object | plot.hstats |
| Plots "hstats_matrix" Object | plot.hstats_matrix |
| Plots "ice" Object | plot.ice |
| Plots "partial_dep" Object | plot.partial_dep |
| Print Method | print.hstats |
| Prints "hstats_matrix" Object | print.hstats_matrix |
| Print Method | print.hstats_summary |
| Prints "ice" Object | print.ice |
| Prints "partial_dep" Object | print.partial_dep |
| Summary Method | summary.hstats |
| Univariate Grid | univariate_grid |
