Package: partykit 1.2-22
partykit: A Toolkit for Recursive Partytioning
A toolkit with infrastructure for representing, summarizing, and visualizing tree-structured regression and classification models. This unified infrastructure can be used for reading/coercing tree models from different sources ('rpart', 'RWeka', 'PMML') yielding objects that share functionality for print()/plot()/predict() methods. Furthermore, new and improved reimplementations of conditional inference trees (ctree()) and model-based recursive partitioning (mob()) from the 'party' package are provided based on the new infrastructure. A description of this package was published by Hothorn and Zeileis (2015) <https://jmlr.org/papers/v16/hothorn15a.html>.
Authors:
partykit_1.2-22.tar.gz
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partykit.pdf |partykit.html✨
partykit/json (API)
NEWS
# Install 'partykit' in R: |
install.packages('partykit', repos = c('https://r-forge.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://r-forge.r-project.org/projects/partykit
- HuntingSpiders - Abundance of Hunting Spiders
- WeatherPlay - Weather Conditions and Playing a Game
Last updated 21 days agofrom:4309c9bb28. Checks:OK: 8 NOTE: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Aug 17 2024 |
R-4.5-win-x86_64 | OK | Aug 17 2024 |
R-4.5-linux-x86_64 | NOTE | Aug 17 2024 |
R-4.4-win-x86_64 | OK | Aug 17 2024 |
R-4.4-mac-x86_64 | OK | Aug 17 2024 |
R-4.4-mac-aarch64 | OK | Aug 17 2024 |
R-4.3-win-x86_64 | OK | Aug 17 2024 |
R-4.3-mac-x86_64 | OK | Aug 17 2024 |
R-4.3-mac-aarch64 | OK | Aug 17 2024 |
Exports:as.constpartyas.partyas.party.rpartas.party.Weka_treeas.party.XMLNodeas.partynodeas.simplepartyas.simpleparty.XMLNodebreaks_splitcforestcharacter_splitctreectree_controldata_partydata_party.defaultedge_simpleextree_dataextree_fitfitted_nodeformatinfo_nodeget_pathsgettreegettree.cforestglmtreeid_nodeindex_splitinfo_nodeinfo_splitis.constpartyis.partynodeis.simplepartyis.terminalkidids_nodekidids_splitkids_nodelmtreemobmob_controlmodel_frame_rpartnode_barplotnode_bivplotnode_boxplotnode_ecdfnode_innernode_mvarnode_partynode_survnode_terminalnodeapplynodeidsnodeprunenodeprune.partypartypartynodepartysplitplot.modelpartyplot.partypmmlTreeModelpredict_partypredict_party.defaultpredict.cforestpredict.modelpartypredict.partyprint.modelpartyprint.partyprob_splitprune.lmtreeprune.modelpartyrefit.modelpartyright_splitsctest.constpartysctest.modelpartysplit_nodesurrogates_nodevarid_splitvarimpvarimp.cforestvarimp.constpartywidth
Dependencies:FormulainumlatticelibcoinMatrixmvtnormrpartsurvival
Constant Partying: Growing and Handling Trees with Constant Fits
Rendered fromconstparty.Rnw
usingutils::Sweave
on Aug 17 2024.Last update: 2019-05-16
Started: 2014-01-15
ctree: Conditional Inference Trees
Rendered fromctree.Rnw
usingutils::Sweave
on Aug 17 2024.Last update: 2021-02-08
Started: 2014-01-15
Parties, Models, Mobsters: A New Implementation of Model-Based Recursive Partitioning in R
Rendered frommob.Rnw
usingutils::Sweave
on Aug 17 2024.Last update: 2020-08-04
Started: 2014-01-15
partykit: A Toolkit for Recursive Partytioning
Rendered frompartykit.Rnw
usingutils::Sweave
on Aug 17 2024.Last update: 2019-05-16
Started: 2013-08-02
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Conditional Random Forests | cforest gettree gettree.cforest predict.cforest |
Conditional Inference Trees | ctree sctest.constparty |
Control for Conditional Inference Trees | ctree_control |
Data Preprocessing for Extensible Trees. | extree_data |
Fit Extensible Trees. | extree_fit |
Generalized Linear Model Trees | glmtree plot.glmtree predict.glmtree print.glmtree |
Abundance of Hunting Spiders | HuntingSpiders |
Linear Model Trees | lmtree plot.lmtree predict.lmtree print.lmtree |
Model-based Recursive Partitioning | coef.modelparty deviance.modelparty fitted.modelparty formula.modelparty getCall.modelparty logLik.modelparty mob model.frame.modelparty modelparty nobs.modelparty plot.modelparty predict.modelparty print.modelparty refit.modelparty residuals.modelparty sctest.modelparty summary.modelparty weights.modelparty |
Control Parameters for Model-Based Partitioning | mob_control |
Model Frame Method for rpart | model_frame_rpart |
Apply Functions Over Nodes | nodeapply nodeapply.party nodeapply.partynode |
Extract Node Identifiers | get_paths nodeids nodeids.party nodeids.partynode |
Panel-Generators for Visualization of Party Trees | edge_simple node_barplot node_bivplot node_boxplot node_ecdf node_inner node_mvar node_surv node_terminal panelfunctions |
Recursive Partytioning | data_party data_party.default is.constparty is.simpleparty names.party names<-.party node_party party |
Coercion Functions | as.constparty as.party as.party.rpart as.party.Weka_tree as.party.XMLNode as.simpleparty as.simpleparty.constparty as.simpleparty.party as.simpleparty.simpleparty as.simpleparty.XMLNode party-coercion pmmlTreeModel |
Methods for Party Objects | depth.party getCall.party length.party nodeprune nodeprune.party party-methods print.constparty print.party print.simpleparty width.party [.party [[.party |
Visualization of Trees | party-plot plot.constparty plot.party plot.simpleparty |
Tree Predictions | party-predict predict.party predict_party predict_party.constparty predict_party.default predict_party.simpleparty |
Inner and Terminal Nodes | fitted_node formatinfo_node id_node info_node kidids_node kids_node partynode split_node surrogates_node |
Methods for Node Objects | as.list.partynode as.partynode as.partynode.list as.partynode.partynode depth.partynode is.partynode is.terminal is.terminal.partynode length.partynode nodeprune.partynode partynode-methods print.partynode width width.partynode [.partynode [[.partynode |
Binary and Multiway Splits | breaks_split character_split index_split info_split kidids_split partysplit prob_split right_split varid_split |
Post-Prune 'modelparty' Objects | prune.lmtree prune.modelparty |
Variable Importance | varimp varimp.cforest varimp.constparty |
Weather Conditions and Playing a Game | WeatherPlay |