Questions tagged [party]

Questions related to regression/classification/model trees created with the R packages party and partykit for recursive partitioning.

Filter by
Sorted by
Tagged with
0 votes
0 answers
21 views

why does the document of ctree only mention “regression”? [closed]

why does the document of ctree only mention “regression”?Actually,ctree can do classification. https://rdrr.io/cran/party/man/ctree.html
Apai's user avatar
  • 1
1 vote
1 answer
24 views

Alpha parameter in model-based recursive partitioning: unexpected results

I have the following code using R partykit package, which yields unexpected results. ...
oartart's user avatar
  • 11
2 votes
1 answer
43 views

prefiltering of predictors using cforest for ctree possible?

I am attempting to create a conditional inference tree using the R-package ctree for a dataset. Unfortunately, the sample size is small and the effects are weak. As ...
teste's user avatar
  • 23
2 votes
1 answer
134 views

partykit::ctree(): Pruning a binary-classification tree based on practical relevance instead of statistical significance

I'm creating a binary classification model to develop relevant segments for a business problem. The ctree-function does a great job, especially in combination with the ...
stats-hb's user avatar
  • 289
2 votes
2 answers
69 views

Checking for significant associations between a mixed set of predictors prior to running a conditional random forest model

I am running a conditional random forest model using the party package in R, with the goal of quantifying variable importance (permutation importance) for 29 predictor variables. My response variable ...
JoeL5475's user avatar
1 vote
1 answer
97 views

Permutation test for mob() tree in partykit

I have data of $N\approx 1200$ whereby treated and control individuals have been matched (via full-matching) as a pre-processing step. This matching step induces correlations between treated and ...
stats134711's user avatar
1 vote
1 answer
269 views

How to compare ctree and cforest approaches on the classification task?

I doing some numerical experiments with ctree() and cforest() functions from the partkid package. I am using the Wine Quality Data Set. ...
Nick's user avatar
  • 858
2 votes
1 answer
82 views

Can model-based recursive partitioning accommodate survey weights?

I am using the model-based recursive partitioning algorithm described in Zeileis, Hothorn and Hornik (2008), available here: https://www.zeileis.org/papers/Zeileis+Hothorn+Hornik-2008.pdf I am using ...
Kate's user avatar
  • 23
3 votes
1 answer
62 views

Influence function used in partykit for binary classification

What is the influence function used for binary classification in the R package partkit, specifically for the conditional tree (...
Kozolovska's user avatar
  • 1,355
1 vote
1 answer
116 views

lmertree: Partitioning factor with too many levels?

I am new to lmertrees. I am having trouble analyzing how individual stimuli in my data clusters together on the basis of how some participants answered to them in three different conditions. My code ...
Miguel's user avatar
  • 13
3 votes
1 answer
269 views

Stability test of MOB algorithm (supLM)

I am interested in better understanding the M-fluctuation test of the MOB algorithm (Zeileis, Hothorn & Hornik, 2008). I have a question regarding the definition of the empirical fluctuation ...
TTT's user avatar
  • 229
1 vote
1 answer
535 views

glmertree to fit logistic regression with two-column y

With both glm and glmer, if I wanted to fit a proportion, I could do it as either: ...
Ramon Diaz-Uriarte's user avatar
2 votes
1 answer
370 views

p-value of multivariate response in partykit::ctree

I wonder if anyone can help me to understand the two questions regarding partykit::ctree: what's the difference between "quadratic" and "maximum&...
blueskyddd's user avatar
3 votes
1 answer
373 views

GLMERTREE with reponse in [0, 1] and multilevel design

I have multilevel data (with nested random effects: (1 | cluster-of-cluster/cluster) in lme4 syntax) where the response is a continuous variable between $[0, 1]$ (i....
Ramon Diaz-Uriarte's user avatar
3 votes
1 answer
228 views

When to use Monte Carlo test type in ctree?

I'm a user of ctree function from partykit package in R. I always wondered for which purpose we want to use Monte Carlo to compute the distribution of test statistics? The literature suggest that it ...
Tom's user avatar
  • 481
1 vote
1 answer
491 views

Variable importance vs significance

I have many predictors and therefore created a cforest and used varimp to determine the most important variable. However, it is not easy for me to interpret the results. One concrete thing I do not ...
eigenvektorin's user avatar
0 votes
0 answers
267 views

How do conditional inference trees calculate p-value when both outcome variable and predictor are binary?

I train a conditional inference tree with binary outcome variable (rent: Y/N) and binary predictors (0 or 1). Here is the output: ...
Beverly's user avatar
1 vote
1 answer
253 views

Can we use glmtree for negative binomial distribution?

I'm trying to create a conditional inference tree predicting number of root grafts in relation to distance between roots and number of roots. My variable response has a negative binomial distribution ...
ElodieROOTS's user avatar
3 votes
1 answer
1k views

Party package (ctree/cforest) in R with NA values

I don't quite understand how ctree/cforest deal with missing predictors. Can someone please explain this further?
Ashti's user avatar
  • 63
3 votes
2 answers
1k views

R result interpretation conditional inference tree result for nominal response

I have nominal responses, "yes/no/don't know", that I am using in a conditional inference tree in R. I am having trouble with how to interpret the model's output concerning one of the independent ...
shea's user avatar
  • 141
2 votes
2 answers
830 views

Ctree in R: how optimal is the optimal split point?

Hi I’m fairly new to using decion trees. I understand that to find the best split points, the ctree algorithm maximises a certain test statistic. I am interested to inspect the values of the test ...
Kai Krabben's user avatar
2 votes
1 answer
203 views

Removal of partitioning variable in final glmtree with new (unused) partitioner -- why?

I'm modeling the likelihood of forest recovery from fire (data here), using glmtrees from the partykit package. I'm quite new to this approach and CV, so I ...
ltlf653's user avatar
  • 109
0 votes
1 answer
321 views

default plot for mob object (glm tree) not returned; using party package [closed]

I'm trying to plot a glm tree using the package party. Per the reference guide, the default plot of the terminal node should be a spinogram as in this image but I ...
ltlf653's user avatar
  • 109
2 votes
1 answer
865 views

Distribution of variable importance in r party package [closed]

I have a dataset of 14558 rows and 250 variables. I am trying to solve a classification problem thanks to r party package and the cforest function (which corresponds to a Random Forest). I would like ...
Rémi Boutin's user avatar
3 votes
1 answer
634 views

Regression tree with nested data repeated in time (GLMERTREE, REEMTREE or REEMCTREE)

I work on the predation of seeds by insects (carabidae), and I am particularly interested in the effect of community composition on predation. I would like to know if the best predation rates are ...
BenjaminC's user avatar
1 vote
1 answer
982 views

Ctree - concerning the splitting criteria

I have a technical question concerning the choice of the splitting criteria for the recursive partitioning. Having selected the most significant variable, I would like to know why the optimal ...
R.B's user avatar
  • 11
1 vote
1 answer
532 views

How to extract the split points of mob() [closed]

In rpart I can simply extract the split points of the tree using ...
Giuseppe's user avatar
  • 1,381
4 votes
1 answer
3k views

Why is random forest performing worse than decision tree [closed]

I have a data set with 1962 observations and 46 columns. Column 46 is the target with 3 classes 1, 2, 3. 6 of the other columns are nominal variables and the rest are ordinal variables. I have ...
Lyndt's user avatar
  • 61
1 vote
0 answers
300 views

Performance of Conditional Inference regression Trees updating the influence function at each node

My goal is to compare the performance of $2$ models of trees using the Conditional Inference tree framework described in (ctree: Conditional Inference Trees), I am following the Partykit 2018. ...
Ismael's user avatar
  • 33
0 votes
2 answers
1k views

Cforest Runs out of RAM when running 'predict' function

I am trying to run the cforest function from the party package in R (or caret, but both have ...
kdunph's user avatar
  • 21
2 votes
1 answer
794 views

Test statistics used for a conditional inference regression tree?

Following the question asked previously about the interpretation of the Test Statistic used for Conditional Inference Trees (What is the test statistics used for a conditional inference regression ...
Ismael's user avatar
  • 33
3 votes
2 answers
684 views

R: Cluster based on similar linear relationships

I'm looking for an unsupervised clustering technique available in R that will allow me to combine repeated measures I have taken at many independent sites, to form subgroups that have similar linear ...
Nick_89's user avatar
  • 35
1 vote
2 answers
2k views

party vs randomForest: large accuracy discrepancy

I have a classification problem where the main aim is maximising classification accuracy. I am using a random forest, and would like to also use the variable importance in my analysis. For this ...
Allan_ZA's user avatar
0 votes
1 answer
568 views

GLMERTREE: confidence intervals for regression coefficients at terminal nodes and implications of fixed effects in lmer/random component

I've built a lmertree model using the GLMERTREE package with random slope and intercept, a treatment variable, and a "partitioning" variable. I've attached a toy dataset and the associated model: ...
Nick_89's user avatar
  • 35
4 votes
2 answers
514 views

Predictors in random Forest

I am building a random forest to predict a binary variable y. I have several predictors named x1..n. One predictor, lets say x1, is a very strong predictor of y but only in some cases (see below) ...
MassCorr's user avatar
  • 173
1 vote
2 answers
4k views

Scale of variable importance in randomForest, party & gbm

I've computed some variable measures using the packages, gbm, randomForest and party. I develop binary classification models predicting survival in cancer patients. Although the gbm package, ...
Jennifer Mente's user avatar
3 votes
1 answer
448 views

GLMERTREE Confidence interval

I am currently analysing a small dataset (see sample data below) using lmertree. My code: ...
Djengis's user avatar
  • 55
3 votes
2 answers
5k views

Decision tree split vs importance

I recently created a decision tree model in R using the Party package (Conditional Inference Tree, ctree model). I generated a visual representation of the decision tree, to see the splits and ...
Mustard Tiger's user avatar
0 votes
1 answer
192 views

GLMERTREE Nested Random effect

Is it possible to include a nested random effect in a formula of glmertree? (https://cran.r-project.org/web/packages/glmertree/glmertree.pdf) I tried it, but it does not seem to work: (R2 should be ...
Djengis's user avatar
  • 55
2 votes
1 answer
182 views

Impact of weights on structural change tests in partykit

I am using the R partykit package to do recursive partitioning of linear regression models and am having trouble understanding how I should expect observation ...
Abiel's user avatar
  • 363
2 votes
1 answer
651 views

Post-Pruning in partykit: the size of mob() tree

I am trying to build a multiple regression model while partitioning my data into subgroups based on additional set of covariates. While I implemented lmtree() or mob() in the "partykit" package, I ...
sunmee's user avatar
  • 23
0 votes
1 answer
248 views

Ctree - law of the test statistics

I am reading the article of Hothorn, Hornik and Zeileis : An unbiased Recursive Partitioning : A conditional Inference Framework. I am interested in using this paper with an objective of regression ...
Pierre Yves Corre's user avatar
1 vote
1 answer
252 views

Regressors vs. conditioning variables in glmtree

I have a dataset with ~800K samples, ~300 features and I'm trying to predict a binary outcome. I've started with sklearn's SGDClassifier (using log loss and l1 ...
Adam Haber's user avatar
0 votes
0 answers
253 views

How to full grow a conditional inference tree using party package

I am currently trying to fit a conditional inference tree using the ctree function in the party package. So far I see that some ...
rivermouth91's user avatar
1 vote
1 answer
304 views

How does evtree choose the root node? [R] [closed]

I'm interested in understanding the mechanism of the Evolutionary Learning of Globally Optimal Trees or evtree in R. Maybe I am missing something, but I don't understand how the root node is chosen ...
user111937's user avatar
3 votes
1 answer
1k views

R Decision Tree based on imbalanced data which was up-sampled

This is a rather theoretical question, so I'm sorry if that's not appropriate to the platform. I have trained a decision tree (partykit) on an imbalanced data set, and to force the model to learn both ...
NRG's user avatar
  • 33
3 votes
0 answers
677 views

cforest prediction taking too long [closed]

I am using the R-package party to build a random forest. The cforest function takes about 5 min to build a random forest model: ...
Ashes's user avatar
  • 31
2 votes
1 answer
6k views

Conditional Inference Random Forest

I use cforest, a function of the R package Party, to realize a conditional inference random forest. However I don't understand how this function compute the predict variable for a regression problem. ...
Axel's user avatar
  • 21
2 votes
1 answer
1k views

In R, does randomForest use terms() of model.matrix?

I am using the randomForest package in R with categorical co-variates. The documentation advises against the formula interface for large data. Following this advice, I prepare the outcome variable ...
Chris's user avatar
  • 625
2 votes
1 answer
989 views

How to calculate variable importance taking correlated predictors into account?

This is the problem I am facing right now: I have a dataset with 100.000 samples and 20 predictors. The predictors are correlated with each other due to their nature. I've run two different random ...
mickkk's user avatar
  • 939