Questions tagged [party]

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

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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 ...
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0 answers
71 views

How to interpret the quantile regression based on random forest?

I have read the Q&A how-are-the-results-of-multivariable-quantile-regression-interpreted and the recommended paper (Petscher and Logan, 2013). I have taken the Wine Quality Data Set, built the ...
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80 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. ...
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  • 850
2 votes
1 answer
45 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 ...
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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 (...
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1 vote
1 answer
55 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 ...
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3 votes
1 answer
124 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 ...
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  • 239
1 vote
1 answer
319 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: ...
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1 vote
1 answer
173 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&...
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2 votes
1 answer
196 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....
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3 votes
1 answer
151 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 ...
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  • 277
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1 answer
294 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 ...
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0 votes
0 answers
161 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: ...
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1 vote
1 answer
144 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 ...
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0 votes
1 answer
871 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?
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3 votes
2 answers
748 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 ...
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  • 141
1 vote
1 answer
525 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 ...
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2 votes
1 answer
124 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 ...
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1 answer
263 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 ...
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  • 89
2 votes
1 answer
713 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 ...
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2 votes
1 answer
444 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 ...
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1 vote
1 answer
707 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 ...
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1 vote
1 answer
456 views

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

In rpart I can simply extract the split points of the tree using ...
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4 votes
1 answer
2k 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 ...
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1 vote
0 answers
239 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. ...
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0 votes
2 answers
857 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 ...
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  • 21
2 votes
1 answer
592 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 ...
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  • 33
3 votes
2 answers
405 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 ...
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1 vote
2 answers
1k 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 ...
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0 votes
1 answer
508 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: ...
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4 votes
2 answers
381 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) ...
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1 vote
2 answers
3k 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, ...
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3 votes
1 answer
343 views

GLMERTREE Confidence interval

I am currently analysing a small dataset (see sample data below) using lmertree. My code: ...
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  • 55
3 votes
2 answers
4k 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 ...
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0 votes
1 answer
152 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 ...
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2 votes
1 answer
151 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 ...
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  • 363
2 votes
1 answer
509 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 ...
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0 votes
1 answer
213 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 ...
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1 vote
1 answer
217 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 ...
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0 votes
0 answers
192 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 ...
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1 vote
1 answer
281 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 ...
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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 ...
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3 votes
0 answers
602 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: ...
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1 vote
1 answer
5k 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. ...
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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 ...
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  • 585
2 votes
1 answer
904 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 ...
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  • 919
2 votes
2 answers
3k views

Plot a subtree from a big decision tree [closed]

I am working on my thesis using decision trees. I am presenting the resulting tree to show how they help in exploring data. My issue is that since the tree is big, I want to break it down into parts, ...
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2 votes
1 answer
546 views

(Boosted) regression trees versus model trees - rule of thumb what to use when

I apply (boosted) regression trees to build predicitive models with continuous outcome (xgboost and gbm). While regression trees ...
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  • 3,286
0 votes
1 answer
2k views

Why does ctree(partykit) perform worse than rpart for a large dataset?

I am trying to solve the same classification problem with the R packages rpart and partykit. I would have expected better ...
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  • 145
3 votes
0 answers
663 views

Missing value handling in cforest in R

I'm trying to build a random forest with 100k records and 2K variables. I have an imputation process to handle missing values while using randomForest but I want to ...
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