20.61 Party Tree
The (Hothorn et al. 2026) package can be used to draw decision trees using partykit::as.party() from (Hothorn and Zeileis 2026) which can be installed from R-Forge:
## [1] "rpart"
The textual presentation of an rpart decision tree can also be improved using party.
##
## Model formula:
## rain_tomorrow ~ rain_today + temp_3pm + temp_9am + cloud_3pm +
## cloud_9am + pressure_3pm + pressure_9am + humidity_3pm +
## humidity_9am + wind_speed_3pm + wind_speed_9am + wind_dir_3pm +
## wind_dir_9am + wind_gust_speed + wind_gust_dir + sunshine +
## evaporation + rainfall + max_temp + min_temp
##
## Fitted party:
## [1] root
## | [2] humidity_3pm < 71.5: No (n=160906, err=13.7%)
## | [3] humidity_3pm >= 71.5
## | | [4] humidity_3pm < 82.5
## | | | [5] wind_gust_speed < 42: No (n=10597, err=36.5%)
## | | | [6] wind_gust_speed >= 42: Yes (n=6884, err=39.9%)
....References
Hothorn, Torsten, Kurt Hornik, Carolin Strobl, and Achim Zeileis. 2026. Party: A Laboratory for Recursive Partytioning. https://codeberg.org/thothorn/party.
Hothorn, Torsten, and Achim Zeileis. 2026. Partykit: A Toolkit for Recursive Partytioning. https://codeberg.org/thothorn/partykit.
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