'Classification And Regression Trees'. CART is a popular data mining technique.

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do CART trees capture interactions among predictors?

This paper claims that in CART, because a binary split is performed on a single covariate at each step, all splits are orthogonal and therefore interactions among covariates are not considered. ...
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12 views

Determine confidence in a CART model with factor (2 levels) response variable (using rpart)

I use the package rpartto model a classification/regression tree. I have the variables $x,y,s$ where $x$ is in $\{-1,1\}$, y is continuous in $[0,1]$ and $s$ is a ...
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23 views

Error message eval(expr, envir, enclos) object 'X1914' not found [on hold]

I have been given two data frames x and y which I used to create two separate corpus ( corpora) Data frame X, has the dependent variable while Y, is the test set with similar variables and headings ...
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9 views

Decision trees: “pchance” at split

I'm reading through Prof. Andrew Moore's Decision Trees tutorial, and I have a question: images of the trees all reference a quantity referred to as "pchance" at the graph splits (see page 19). This ...
3
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24 views

why do decision tree packages convert factor variable into two binary variables

Why are decision tree packages like say, rpart slow with increasing the number of factor levels in R. I read that it basically converts each factor variable into two binary variables representing ...
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17 views

predict for rpart model [closed]

I do cross validation for doing rpart model, exactly I do leave one out(LOO)(one row fro testing teh model and the others for learning teh model) so the testing set will consist of one row for each ...
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34 views

“Complete” classification using decision tree

While exploring the examples from "Practical Data Science with R", I am using a decision tree to classify the spambase dataset. It works fine, but I am trying to "abuse" the model in order to have ...
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1answer
38 views

Interpret learning curves

I am training a Decision Tree on a dataset of around 580.000 data points. I took the following steps: Split the dataset in training (75%) and validation (25%) set. Determined the best depth for the ...
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2answers
44 views

Predictive Decision Tree in R

I am currently working on a dataset in R-studio and as the title might suggest I am having difficulty creating the tree I'm looking for. My dataset consist of 122151 observations with 33 Variables. ...
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37 views

Clustering algorithm when we already know what sort of clusters should be formed?

Normal clustering algorithms like k means are given no information about what sort of clusters are to be formed. However, I am looking for a clustering algorithm which will cluster into groups that I ...
0
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1answer
27 views

Tree model with poisson distributed response variable

If I understand correctly the R tree model - library(tree) - can only be used if the response variable is normally distributed. Is there a way to create a tree model with poisson distributed response ...
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1answer
30 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 ...
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49 views

Classification & Regression Trees (CART)

It seems that most CART examples I encounter involve splitting the sample into a training sample and test sample. This split sample method strikes me as terribly inefficient unless you have a large ...
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24 views

Training and testing a Decision Tree Learner, can linear regression help obtain an optimal partition?

In class we are seeing decision tree learners and as a project I implemented from scratch my version of the one taught to us. I am using the famous Titanic Survival data (~1000 lines) for training and ...
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13 views

Plotcp Plot Plateaus

I'm trying to understand why this graph plateaus. I have many more levels in the predictors than there are splits, so I'm confused why the tree stops splitting at only 447. I'm also confused why the ...
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25 views

Why added predictors improved performance in decision trees if they don't appear in the model?

although I've been working some months now with decision trees, I still have issues understanding some things and also finding a right source to answer my questions. Maybe I'm not using the right ...
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1answer
36 views

Meaning of `max_depth` in GradientBoostingClassifier in scikit-learn

when I use the GradientBoostingClassifier from scikit-learn, I find that there is a parameter max_depth to set, which controls the maximum depth of the regression ...
0
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1answer
20 views

How to choose a regression tree (base learner) at each iteration of Gradient Tree Boosting?

I'm trying to understand Gradient Tree Boosting, by following Prof. Friedman's original paper: Greedy Function Approximation: A Gradient Boosting Machine. Basically, at each iteration, a regression ...
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16 views

Generating a good training dataset for decision tree building

I am building a decision tree predicting the accuracy score of an image processing algorithm, based on a number of image parameters. I have identified 6 uncorrelated parameters that impact the ...
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1answer
43 views

Is the rpart CART algorithm deterministic? Why are the plots for the CP different?

I'm fitting regression and classification trees. I thought that the algorithm to fit the tree led to the same result each time. However, when I run the line below ...
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1answer
106 views

Advantage of GLMs in terminal nodes of a regression tree?

So I'm playing around with the idea of writing an algorithm that grows and prunes a regression tree from the data and then, in the terminal nodes of the tree, fits a GLM. I've been trying to read up ...
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21 views

Do i need equidistant time intervals for classification task?

I have a dataset of the following structure and want to use it for a classification task. The first column contains the timestamp when the values were measured. As you can see only data changes are ...
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16 views

Splitting variable selection in regression trees

I am struggling to determine how the further partitioning of nodes in a regression tree works. I have figured out how the initial splitting variable and split point at the root node are selected, but ...
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36 views

C4.5 How to select the split point (threshold) for a Continuous Attribute

Using the "play golf" or "play ball" data (listed at the bottom), to pick the root node we look at Outlook, Temperature, Humidity, and Wind, to see which has the highest GainRatio. Now, Outlook will ...
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1answer
20 views

When is classification error rate preferable when pruning decision trees?

I'm going through Chapter 8 of "Introduction to Statistical learning" which introduces decision trees. My question is specific to the three approaches to pruning a decision tree (i.e., classification ...
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Tree Pruning Tuning Parameter

Suppose I have grown a full decision tree and now I want to define a sub-tree that prunes back the full tree. Let $T$ be the number of terminal nodes for a given sub-tree, then the pruning ...
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1answer
47 views

Logistic regression before decision tree model

I am trying to run several decision tree models (CHAID, C&RT, QUEST), but I have learned that several researchers have applied logistic regression model first in order to select risk factors. So, ...
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26 views

why boosting method is sensitive to outliers

I found many articles showing that boosting methods are sensitive to outliers, but no article explains why. In my experience, I feel outliers data is bad for any machine learning algorithms, but why ...
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1answer
60 views

Should I use Mean Square Error or Classification Rate?

I am a self-taught person and I would like your help. I am learning about predictive modeling in general, and I'm also trying to do predictive modeling for a specific problem. I am exploring ...
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34 views

Correlation between decision trees

How do you find the correlation between decision trees? I know this is an issue when working with random forests, but I can't find an explicit formula anywhere. I only get that random forest reduces ...
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20 views

Non-recursive regression tree

I would like to construct a regression tree such that each factor appears at most once on each branch. When I use rpart in R, it commonly results in a tree where ...
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1answer
34 views

Regression trees to model rates

I am performing a predictive modeling application where I have to predict claims. If I had used classical GLMs, I would have used a poisson glm using log exposure as offset, assuming therefore ...
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1answer
29 views

Using regression tree on time series data

I have been looking around for resources on applying a regression tree in an attempt to understanding how various spend variables impact a companies revenue overtime. Is this type of analysis ...
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18 views

Decision tree indicating payoffs

I need to draw a decision tree to represents these requirements : The research and development manager in an old oil company, which is considering making some changes, lists the following courses of ...
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1answer
241 views

Does the number of rows really matter beyond a point?

While working with any machine learning algorithm, does the number of rows really matter beyond a certain point? I have kept some algorithms(decision tree in this instance) running for days, and the ...
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21 views

CHAID tree analysis in SPSS

I am trying to build a decision tree using CHAID in SPSS. I am however getting only one node. I have tried taking several data inputs. I also tried out CRT. Is there some setting that needs to be done ...
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48 views

Why do Matlab's TreeBagger and fitensemble with 'bag' and same parameters give different predictions

Matlab's Statistical Toolbox has two bagging tree algorithms implementation: Tree Bagger Fitensemble (see 'Bag' method) I am currently using (1) for a Regression problem. However, I would like to ...
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33 views

Do classification trees need to consider the correlation between attributes?

In decision tree classification, we use the attribute that splits records, like entropy, as split nodes. Does it need to consider the correlation between attributes?
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1answer
32 views

number of rules from a classification tree?

I have generated a classification tree for a dataset using classregtree method in matlab. Tree gives me rules explained by if and elseifs. For a tree, i want to calculate number of rule generated from ...
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what do you think about the capability of decision trees on the data labels are the sum of features?

Let me assume a data where each instance has a label that is the sum of its feature values. I believe in such a easy problem decision trees have very hard times. What do you think for such an argument ...
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33 views

Represent decision tree as matrices

Is it possible to use matrix operations to generate node membership for decision trees? In a binary decision tree, each node represents a condition for a single variable. Ignoring the more complicated ...
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56 views

How to fit Decision Tree classifier for highly imbalanced response variable?

I use R, Party package in order to fit prediction model ("classifier") for "Converted.clicks" as response variable. The rest of vars are used as explaining variables in the model. Here is the ...
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54 views

What do these decision boundaries indicate in random forest and svm?

I was working on data science harvard homework problem. It is a two class classification problem in which they plot the decision boundary for random forest, svm and decision tree. The problem has 2 ...
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34 views

Understanding cost-complexity pruning in regression trees

I am trying to understand how an optimal tree length is determined using cost-complexity pruning. Visit this lecture note screenshot: ...
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2answers
52 views

Predictive Model - Increase Pediction Accuracy for Less Likely Events

I am trying to build a model that predicts the which binary category a respondent belongs to (0 or 1). I have demographic variables (all categorical) and a few 10 point questions. I have built a few ...
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1answer
65 views

How does caret handle factors?

I have been testing conditional trees and random forests with caret, and I've noticed it does something weird with factors. So, for example, a ctree using the base dataset ...
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1answer
28 views

Decision Tree English Rules and Dependency Network in MS SSAS

I created a Decision Tree model in Microsoft Analysis Services (SSAS, Visual Studio 2010). There are two tabs in the Mining Model Viewer tab: (1) Decision Tree that shows a tree itself, and (2) ...
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12 views

Why is MeanDecreaseGini over 1 in RandomForest package in R? [duplicate]

I am using R package randomForest, and calculated MeanDecreaseGini as below. ...
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1answer
48 views

How are individual trees added together in boosted regression tree?

I'm reading Introduction to Statistical Learning, James, G., et al. (2013), in which they describe the Boosted Regression Tree algorithm as following. What I do not understand is Eq 8.10 and 8.11. ...
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1answer
44 views

Extract training data predictions from rpart

I'm wondering if there is any method to extract the class assignment of each sample in an rpart model from the training data? E.g. in R using random forest to get the predicted class of each sample ...