{treeheatr}
an R package for interpretable decision tree visualizations
🌳
🔥
Trang Le, Jason Moore
University of Pennsylvania
@trang1618
Your decision tree    may be cool, but what if I tell you
you can make it hot?
🌳
🔥
decision tree + heatmap
rpart.plot
Terry Therneau, Beth Atkinson, Brian Ripley
visNetwork::visTree()
Almende B.V., Benoit Thieurmel , Titouan Robert
partykit::plot.party()
Torsten Hothorn, Heidi Seibold, Achim Zeileis
ggparty
Martin Borkovec, Niyaz Madin, et al.
dtreeviz
(Python)
Terence Parr, Prince Grover
treeheatr
treeheatr::heat_tree(x)can be of object
-
party (or constparty)
specifying the precomputed tree -
partynodeÂ
specifying the manual tree - data.frame (or tibble)
heat_tree(x, target_lab = 'Outcome')351 blood samples (January 10 - February 18)
3 features:
- lactic dehydrogenase (LDH)
- lymphocyte levels
- high-sensitivity C-reactive protein (hs_CRP)
COVID-19 patient data
heat_tree(x = covid, target_lab = 'Outcome')data.frame
heat_tree(covid, target_lab = 'Outcome',
feats = NA)
split_ldh <- partysplit(1L, breaks = 365)
split_crp <- partysplit(2L, breaks = 41.2)
split_lymp <- partysplit(3L, breaks = 14.7)
custom_tree <- partynode(1L, split = split_ldh , kids = list(
partynode(2L, split = split_crp, kids = list(
partynode(3L, info = 'Survival'),
partynode(4L, split = split_lymp, kids = list(
partynode(5L, info = 'Death'),
partynode(6L, info = 'Survival'))))),
partynode(7L, info = 'Death')))
heat_tree(x = custom_tree, data_test = covid, target_lab = 'Outcome')
Thanks!
@trang1618
Funding
NIH LM010098
NIH AI116794
R packages
ggplot2
partykit
ggparty
heatmaply
People
Jason Moore
Anonymous reviewers