Questions tagged [party]
Questions related to regression/classification/model trees created with the R packages party and partykit for recursive partitioning.
58
questions
1
vote
1
answer
28
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 ...
- 672
0
votes
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 ...
- 850
1
vote
1
answer
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.
...
- 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 ...
- 23
2
votes
1
answer
24
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 (...
- 1,055
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 ...
- 13
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 ...
- 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:
...
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&...
- 175
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....
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 ...
- 277
1
vote
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 ...
- 13
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:
...
- 3
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 ...
- 11
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?
- 13
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 ...
- 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 ...
- 11
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 ...
- 89
0
votes
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 ...
- 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 ...
- 23
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 ...
- 21
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 ...
- 11
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
...
- 1,211
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 ...
- 61
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.
...
- 33
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 ...
- 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 ...
- 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 ...
- 35
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 ...
- 35
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:
...
- 35
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) ...
- 173
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, ...
- 135
3
votes
1
answer
343
views
GLMERTREE Confidence interval
I am currently analysing a small dataset (see sample data below) using lmertree.
My code:
...
- 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 ...
- 215
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 ...
- 55
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 ...
- 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 ...
- 23
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 ...
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 ...
- 23
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 ...
- 41
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 ...
- 25
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 ...
- 33
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:
...
- 31
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.
...
- 11
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 ...
- 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 ...
- 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, ...
- 41
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 ...
- 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 ...
- 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 ...
