Questions tagged [party]
Questions related to regression/classification/model trees created with the R packages party and partykit for recursive partitioning.
2
votes
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
...
