Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [party]

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

56 questions
7
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2 answers

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): require(randomForest) require(party) require(RCurl) x <-…
mguzmann
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5
votes
1 answer

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 can improve them. I am growing a big tree (alpha = 0.9) and pruning with AIC as the criterion. I am using the AUC (pROC…
Dani
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5
votes
1 answer

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 categories and numerical predictors?
goldisfine
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4
votes
1 answer

Why is random forest performing worse than decision tree

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 preprocessed them using as follows: for (i in…
Lyndt
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4
votes
2 answers

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) while the others x2..n are fair predictors in all…
MassCorr
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4
votes
1 answer

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 trees as well ("party" package in R) Now, under…
Dataminer
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3
votes
2 answers

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 variables: gender. There are other independent…
shea
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3
votes
2 answers

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 relationships (in terms of slope not intercept)…
Nick_89
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3
votes
2 answers

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 levels. I also computed the variables importance using…
Mustard Tiger
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3
votes
1 answer

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 positive and negative examples I have up-sampled…
NRG
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3
votes
0 answers

cforest prediction taking too long

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: cf.model <- cforest(as.factor(y) ~ ., data = train.data, controls = cforest_control(ntree = 25, maxdepth = 6)) However,…
Ashes
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3
votes
0 answers

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 understand what exactly happens to missing values in predictors in cforest. I looked…
Sourav Sarkar
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2
votes
1 answer

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 survey data, which requires that I use…
Kate
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2
votes
1 answer

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 (ctree). I could not find any details in the R package documentation. In the vigente I found this paragraph about…
Kozolovska
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2
votes
1 answer

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 process, $W_{j}(t)$, and then the supLM test that is…
TTT
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