Questions tagged [party]
Questions related to regression/classification/model trees created with the R packages party and partykit for recursive partitioning.
54
questions
2
votes
1answer
12 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
vote
1answer
36 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 ...
2
votes
1answer
91 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 ...
1
vote
1answer
236 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
1answer
110 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&...
2
votes
1answer
153 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....
2
votes
1answer
109 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 ...
1
vote
1answer
210 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 ...
0
votes
0answers
128 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:
...
1
vote
1answer
105 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 ...
0
votes
1answer
731 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?
3
votes
2answers
606 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 ...
1
vote
1answer
405 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 ...
2
votes
1answer
110 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 ...
0
votes
1answer
227 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 ...
2
votes
1answer
625 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 ...
2
votes
1answer
366 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 ...
1
vote
1answer
626 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 ...
1
vote
1answer
418 views
How to extract the split points of mob() [closed]
In rpart I can simply extract the split points of the tree using
...
4
votes
1answer
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 ...
1
vote
0answers
219 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.
...
0
votes
2answers
793 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 ...
2
votes
1answer
519 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 ...
3
votes
2answers
269 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 ...
1
vote
2answers
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 ...
0
votes
1answer
470 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:
...
4
votes
2answers
355 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) ...
0
votes
2answers
2k 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, ...
2
votes
1answer
295 views
GLMERTREE Confidence interval
I am currently analysing a small dataset (see sample data below) using lmertree.
My code:
...
3
votes
2answers
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 ...
0
votes
1answer
136 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 ...
2
votes
1answer
139 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 ...
1
vote
1answer
441 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 ...
0
votes
1answer
203 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
1answer
199 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 ...
0
votes
0answers
178 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 ...
1
vote
1answer
274 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 ...
3
votes
1answer
999 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 ...
3
votes
0answers
551 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:
...
1
vote
1answer
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.
...
2
votes
1answer
867 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 ...
1
vote
1answer
863 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 ...
2
votes
2answers
2k 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, ...
2
votes
1answer
543 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 ...
0
votes
1answer
1k 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 ...
3
votes
0answers
642 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 ...
1
vote
0answers
285 views
Reporting variable importance results using cforest
I have a large data set of odour samples. I used cforest and varimp to determine the most important variables (ie chemical compounds) in identifying sex.
How do I report this in a paper? Do I need to ...
5
votes
1answer
2k views
Evaluate glmtree model
I am using the glmtree function from the partykit package in R.
I would like to know how I can evaluate the models and how I ...
2
votes
1answer
1k views
How do Conditional Inference Trees do binary classification?
I am trying to learn about Conditional Inference Trees, and have been doing some very simple comparisons of the ctree() and rpart() functions in R. I have looked at the documentation for ctree(), but ...
7
votes
2answers
7k views
Variable importance in party vs randomForest
I am getting completely different results from cforest and randomForest with regards to variable importance (mean decrease in accuracy):
...
