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.

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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 ...
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16 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 ?
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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%
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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 ...
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P(node) in rpart

I am going through rpart doc and came across P(node). I cannot understand what it means: Here is illustration: ...
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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 ...
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How to interpret 'estimated rate' in recursive pationing analysis used for survival analysis in R /rpart?

I am using rpart for a survival analysis. I am not sure how to interpret the value labeled 'estimated rate' in a RPA used for survival analysis. I have ...
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20 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 ...
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24 views

How can the balanced accurcay be bigger than the normal accuracy in unbalanced test data? [duplicate]

I constructed two binary classification tree's on two different training set's that i balanced with oversampling and undersampling. The test set is still unbalanced. After that i computetd the ...
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45 views

What is the objective function in cost-complexity pruning in rpart for classification tree?

I constructed a classification tree and want to prune it by using cost-complexity pruning in the rpart package. The objective function of cost-complexity prunig is C(T)=L(T)+a|T|. For regression tree ...
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Why different seeds produce different mse values for regression tree and ols?

I compare regression tree and ols in terms of out of sample prediction. I realized that the mse values changed when i change the seeds before getting train and test set. Sometimes ols is better ...
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39 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 ...
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Calculating precision and recall performance metrics in a classification tree analysis in R

I'm posting here as I suppose the topic of my question is more relevant for this forum, although please let me know if I'm wrong. I'm reformulating a previous question I posted in the R forum with ...
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219 views

Understanding a Classification Tree applied to the iris dataset

I used the iris dataset for a simple regression tree to see how things work. I am generally interested in two aspects: Why does the tree not use the Sepal data to improve the classification What do ...
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104 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 ...
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215 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,...
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533 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 ...
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163 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 ...
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118 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. ...
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280 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 ...
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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. ...
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1answer
886 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 ...
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16k 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.... ...
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5k 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 ...
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1answer
55 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. ...
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925 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....
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490 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 ...
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1k views

how to interpret value.importance for an rpart object

How can I interpret the values for the variable.importance in a rpart object? ...
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726 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: ...
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282 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, ...
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1answer
59 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 ...
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1answer
627 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 ...
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1answer
357 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 : ...
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1answer
906 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 ...
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1answer
107 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 ...
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135 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 ...
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1answer
587 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 ...
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13k 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 ...
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1k 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. ...
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1answer
365 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 ...
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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 ...
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236 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 ...
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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 ...
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955 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 ...
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86 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 ...
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1answer
610 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 ...
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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 ...
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1answer
913 views

variable importance in boosted regression tree

I have trouble understanding how relative influence of a variable is calculated in a boosted regression tree. I am reading from the following paper by Friedman and Meulman. Multiple additive ...
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1answer
140 views

Minimizing Single-Class Classification Error in R Trees

I'm running tree models in R to help define rules for predicting a binary outcome (0 or 1, of course). I understand mostly how to algorithm works, but I'm in a position where I don't really care about ...
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10k views

Performance of regression tree rpart

I am running a regression tree using rpart and I would like to understand how well it is performing. I know that rpart has cross validation built in, so I should not divide the dataset before of the ...