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Questions tagged [party]

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

2
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2answers
40 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 ...
0
votes
1answer
26 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 ...
1
vote
1answer
27 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
55 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 ...
1
vote
1answer
60 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
133 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 ...
0
votes
1answer
140 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 ...
0
votes
1answer
169 views

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

In rpart I can simply extract the split points of the tree using ...
0
votes
0answers
46 views

Variable Importance for Random Forest: Interpreting raw values?

It is sometimes stated that one does not care about the ''raw'' values of the variable importance outcome: PI(X_j):=MSE_nonRandomlyAssigned(X_j)-MSE_RandomlyAssigned(X_j) for each feature X_j using ...
4
votes
1answer
373 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
76 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
317 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 ...
1
vote
1answer
187 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 ...
2
votes
2answers
70 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 ...
0
votes
2answers
636 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
208 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
210 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
666 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, ...
0
votes
1answer
161 views

GLMERTREE Confidence interval

I am currently analysing a small dataset (see sample data below) using lmertree. My code: ...
2
votes
2answers
2k 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
93 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 ...
1
vote
1answer
75 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 ...
0
votes
1answer
176 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
164 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 ...
0
votes
1answer
92 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
134 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 ...
0
votes
1answer
186 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
600 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
319 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: ...
0
votes
1answer
3k 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. ...
1
vote
1answer
477 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
605 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 ...
1
vote
2answers
1k 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, ...
0
votes
1answer
477 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
980 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 ...
2
votes
0answers
516 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
222 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 ...
3
votes
1answer
1k 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 ...
1
vote
1answer
815 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 ...
4
votes
2answers
5k 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): ...
0
votes
0answers
334 views

plotting prediction in trees of glm of partykit package

I am using partykit R package to perform a trees of poisson regression. I would like to have the estimated (predict with ...
2
votes
1answer
3k views

Pruning Conditional Inference Trees

I am trying to build a prediction model using classification trees. While I tried the "rpart" package, the results were not entirely satisfactory. Hence, I thought of exploring conditional inference ...
3
votes
1answer
1k views

What is the test statistics used for a conditional inference regression tree?

In Hothorn et al, the test statistic is specified as $$ T_j(L_n, w) = vec(\sum w_i g_j(X_{ji}) h(Y_i, (Y_1,...,Y_n)^T))$$ What is the exact form of this test statistic with a continuous response and ...
1
vote
0answers
766 views

increase the speed of random forest conditional importance from the party R package

I have a dataset with numerical and categorical variables and a binary output variable. I want to use the conditional importance in random Forest This is my code ...