Questions tagged [rpart]

`rpart` is an R package that provides a number of routines related to regression trees and recursive partitioning algorithms. This package is frequently used for classification problems.

Filter by
Sorted by
Tagged with
-1
votes
0answers
21 views

Classification and Regression tree

Please how do I start and where do I end. I am having trouble interpreting this classification plot. However, I started with this ..... At the top node of the tree, for the variable absent days term, ...
1
vote
1answer
20 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
0answers
9 views

How to interpret output of rpart model with survival object as response?

What do the numbers in terminal nodes represent? And how to interpret the predicted value for new observation obtained from function predict() ?
0
votes
0answers
12 views

How to interpret/determine interactions via decision trees?

I was curious how you would determine/interpret whether variables in your decision tree are interacting or not? ...
1
vote
1answer
74 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....
0
votes
0answers
15 views

Almost identical errors for cp=0 as for cp=1 in rpart decision tree

I am trying to build a decision tree based on insurance, frequency data (assumed to be poisson distributed, around 200K observations) using the rpart package in R. Now I have tried to build a tree ...
0
votes
0answers
24 views

High xerror in regression tree

I am building a regression tree model on a frequency data set using the rpart package. However, when I evaluate the model I get xerrors very close to one for each split (see table below). Because I am ...
1
vote
1answer
32 views

Why is the error rate from bagging trees much higher than that from a single tree?

I'm running the classification method Bagging Tree (Bootstrap Aggregation) and compare the misclassification error rate with one from one single tree. We expect that the result from bagging tree is ...
0
votes
1answer
21 views

Regression trees with geepack package

I can’t run regression trees without geeglm. I have longitudinal data so rpart wouldn’t work. Is there a way to get regression trees with geeglm?
0
votes
0answers
214 views

classification with rpart: why my confusion Matrix is not working?

I have a data set of 699 rows and in the exercise I'm working on it is requested to generate a training set of 300 observations. The rest will be the test set. I write all the possible information in ...
1
vote
1answer
23 views

How does decision tree decide which variable to use in next split?

The CART (or RPART) algorithm uses gini index to find a threshold value for a variable in each split. But how does it choose which variable will it use for splitting ?
0
votes
0answers
16 views

Decisions Tree - JOINT Probability rpart

Please describe if I could calculate joined probability for No class. I am using R and rpart. I want to check how probability will change if I make cuts under my tree like attached. 73%*34% + 71%*22%
0
votes
0answers
8 views

Should I prune the tree trained on parameters obtained by Bayesian Optimization?

If the parameters for a decision tree are obtained by bayesian optimization, where the 10-fold cross validation error is minimized (or 1- error maximized) and afterwards the model is trained on the ...
0
votes
0answers
19 views

P(node) in rpart

I am going through rpart doc and came across P(node). I cannot understand what it means: Here is illustration: ...
1
vote
2answers
84 views

Does it make sense to use bayesian optimization for tuning of hyperparameters of decision tree model?

Does it make sense to use bayesian optimization for tuning of hyperparameters of decision tree model? I have not found any article or anything related to this, as BO is usually used for black-box ...
1
vote
0answers
37 views

R: rpart or random forest for datasets with multiple rows per subject [closed]

I have some fundamental understanding problem with rpart or train(method="rf") in R. My data is currently structured as follows: Around 100 subjects, each has 2048 rows (so around 204,800 rows) with ...
0
votes
1answer
63 views

When does OLS Regression outperform regression tree in term of out of sample prediction?

In my Master thesis i compare ols regression to regression tree to predict wages. I thought that i will get better prediction with the regression tree because it cathes more interactions. But now i ...
1
vote
0answers
144 views

Rpart and subsets

I am getting unexpected results from an rpart model, where the model selects two variables, one of which is a subset of the other. This in itself is not unexpected, but the seemingly odd thing is that ...
1
vote
0answers
355 views

Why do RMSE values increase on a smaller tree (RPART)

AIM: I want to understand why does RMSE increase on a smaller tree. CONTEXT: I am learning the rpart algorithm. I had some data,...
0
votes
0answers
716 views

Metrics in rpart decision trees

I am currently working with decision trees in R, I am using caret library. Source code of rpart can be found here: https://github.com/cran/rpart/blob/master/R/rpart.R I understand how decision trees ...
0
votes
2answers
217 views

classification tree with rpart()

I'm using the rpart() to build a classification tree using R. I have no experience in this topic... Anyway, I started with the full model, and then I used the varImp() from "caret" to drop some ...
1
vote
0answers
161 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. ...
2
votes
1answer
376 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
0answers
61 views

Is rpart randomizing the variables it tries as splits?

I am fitting a decision with rpart on R. I have many variables and it seems to me that it would take a long time for rpart to try them all at every step, to determine what the next best split is. ...
3
votes
1answer
1k views

Are decision trees sensitive to log translations in feature space?

This question was partially answered on Are decision trees sensitive to translations in feature space?, but no references were provided for "Gini impurity and entropy measures are translation ...
4
votes
0answers
19k views

Interpretation of Rpart for Decision Trees

I recently used rpart for an R-decision tree, but am confused on how to read the results.... ...
2
votes
0answers
6k views

Decision Tree in R: rpart on categorical variables

Introduction: I would like to build a classifier which distinguishes between buyers and non-buyers based on user behavior. This data is highly imbalanced (0.009% for positive class), and I'm ...
1
vote
1answer
56 views

Classification in R - seperate category for uncertain classifications

I am constructing classification trees for the first time, so I'm quite new to this use of R. I have observations of behaviours and incoming data that has to be classified as one of these behaviours. ...
0
votes
0answers
1k views

discretization to create intervals for continuous variables

I am new to R and have basic stats understanding. Please excuse me if my questions are basic in nature. I am learning and having these questions and your answers would help me in updating my knowledge....
1
vote
1answer
525 views

Use decision tree to learn precise classification rules: need accuracy of 1

I'm trying to use a decision tree algorithm to learn how general ledger transactions (10 digit code) are classified into revenue, expense, G&A et cetera without actually scripting every ...
1
vote
0answers
2k views

how to interpret value.importance for an rpart object

How can I interpret the values for the variable.importance in a rpart object? ...
1
vote
1answer
855 views

How can I use estimated probabilities of a class from rpart to identify the top N classes?

Using the rpart library, I'm trying to predict which class each observation belongs to. Here is a reproducible example explaining the steps I am taking: ...
4
votes
1answer
315 views

Disrepencies between Information Gain and Tree Growth

I was wondering if someone can explain to me why in my decision tree some of the variable with the highest importance (highest information - script shown below) do not appear into my tree at all, ...
0
votes
1answer
62 views

What does a decision tree with both GOOD outcome means?

I have a decision tree built in R using rpart() from rpart package. However, when following the nodes, we have one condition leading to both outcomes as GOOD. This is weird for me. What does that ...
2
votes
1answer
769 views

Handle missing value in continuous variable in Decision Tree without losing its meaning

I want to train a Decision Tree model with a dataset, of which some of the continuous variables contain missing values. I want to preserve the meaning of missing value while training, meaning that ...
1
vote
1answer
462 views

Understanding rpart package - unexpected behavior when swaping two columns in explanatory varaibles table

I have a problem understanding the behavior of rpart function of R. Here is the r code part : ...
0
votes
1answer
1k views

Loss matrix to be included in decision tree? Rpart -R

For loss matrix, is it necessary to include it during the decision tree analysis ? What will be the impact if this is excluded from the analysis e.g loss matrix (0,1,1,0) in Rpart-R? Do we usually ...
0
votes
1answer
142 views

Continuous output instead of classification

I was trying to do some classification problem where target variable should be one of 4 classes. I tried rpart and ranger ...
1
vote
0answers
173 views

Classification tree cross val error increasing but test error decreasing

My data has 5000 points. I predict a categorical outcome using 10 numeric variables. I build a tree with 3500 points (in R using rpart) using cross validation and plotcp shows this below ... I have ...
0
votes
1answer
679 views

Use of regression-trees to determine probabilities for a binary variable

I have a binary variable (sold/not sold) and I have used the CART algorithm in R (rpart) to build a classification tree to predict if this product is getting sold or not. Now I would like to add a ...
5
votes
1answer
16k views

rpart, Cross Validation. [closed]

I have a question of using the rpart for the regression tree. I am wondering when i use plotcp, where would my validation data comes from? Currently, I have a ...
0
votes
0answers
2k views

What is the formula of varImp in R?

I'm using varImp function(caret package) in R to get importance of variables and to select variables. I know how can i get result. This is my code and result. ...
1
vote
1answer
409 views

Rpart regression tree using aggregate data instead of record level data – The results are not the same

I have a large dataset (over 6 million records) and I have aggregated the dataset (dplyer package) and tested rpart() on the two ...
2
votes
1answer
1k views

Decision tree with imbalanced data not affected by pruning

I am looking to use a Decision Tree to classify whether or not a car will sell based on attributes of that car. The attributes that I have include price, year, mileage, condition (new, pre-owned, or ...
0
votes
0answers
318 views

How to make a regression model for a relation looking like a step function ? Why can't I get an output for recursive partitioning done below?

I'm working on a dataset to describe the relationship between length and age of bluegill fish and the linear model based plot looks like this: I hence tried using recursive partitioning algorithm as ...
2
votes
1answer
2k views

R, rpart(), classification tree, cptable$xerror [closed]

i randomly split my data into training and test sets. then using the training set, i construct an overfitting classification tree with 10-fold cross-validation. i.e. xval=10 and prune it (with ...
4
votes
1answer
1k views

Handling of categorical variables: rpart vs tree

For tree and randomForest packages in R, the number of levels for a factor (as a categorical variable) is capped at 32. An explanation might be that the number of comparisons at each split becomes ...
0
votes
0answers
119 views

how do you calculate the number of combinations recursive partitioning uses in decision trees?

So I was wondering why random forests limit the levels of a variable to 32 levels, and I found an answer here : R's randomForest can not handle more than 32 levels. What is workaround? My ...
0
votes
1answer
722 views

Predicting from RPart using a subset of variables

I fitted a RPart model from all of a couple dozen variables. Now, I want to test predictions using just a couple of variables that seem significant to me. If it was the iris dataset, for example, I ...
2
votes
1answer
3k views

How to improve my classification tree ? R

I have a database with 1200 observations and 14 variables and I'am trying to do a classification tree for my dependent nominal variable who hase 4 modality ...