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

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cross validation for cart

When a dataset is given and it is divided into N parts, training a Cart on N-1 parts and testing it on the remaining part (and doing that N times, i.e. for each possible leave-out), one ends up with N ...
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9 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 ...
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Weka class attribute [on hold]

We are trying to run J48 on a classified data set. Our class attribute has two possible values ( 0,1) when running J48 the tree terminates at the very first node and doesnt process any further. ...
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7 views

Likelihood estimator for JMP decision trees

In the documentation for JMP decision trees- it details that the calculation for the "Entropy RSquared" (Actually McFadden's $R^2$) is calculated thus: $R^2 = -2\log(L_m/L_0)$ Where $L_m$ and $L_0$ ...
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Classification and regression tree (CART) on large data set

I am trying to approximate a multivariate function $y = f(x_1, ...x_n)$, which I have reason to believe will be well approximated by a classification and regression tree. Some of the variables are ...
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19 views

Decision tree analysis in SPSS

I am newbie in the field of analytics so my question could be naive. I tried searching the answer before posting but could get my hands on the exact answer I am looking for. I have a simple model to ...
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1answer
56 views

How to use decision stump as weak learner in Adaboost?

I want to implement Adaboost using Decision Stump. Is it correct to make as many decision stump as our data set's features in each iteration of Adaboost? For example, if I have a data set with 24 ...
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7 views

How to compute a consensus tree from RandomSurvivalForest object?

Is it possible to compute a consensus tree from a Random Survival Forest object using R? Please note I don't mean Random Forest, but Random Survival Forest. Which R packages are necessary or which ...
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30 views

Force start with specific root node using decision trees in R

I'm using decision trees in R, with library("party") ctree.dt <- ctree(Pasillo_Ataque_2T ~ Dist_Col_1T + Dist_1T_2T, data=dt) And it produce: It's ...
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21 views

Comparing models on two target variables

I have a dataset with two binary target variables $Y_a$ and $Y_b$. I can build two classification tree models: $\hat{Y}_a = M_a(X)$ $\hat{Y}_b = M_b(X)$ Questions: Is there a way to compare the ...
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26 views

Rule based classification

I have dataset with continuous, ordinal & nominal variables features (v1 to vn) and a binary outcome variable (red/green). The task is to identify top N "rules" that influence/indicate the ...
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Minimum description length principal (MDLP) stopping criterion with repeated values

Fayyad's paper on discretization of continuous attributes describes a canonical way to discretize continuous attributes using a minimum entropy method. However, the paper does not describe what to do ...
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44 views

Predictions for rpart model require more variables than shown in the classification tree

Using rpart from the caret package, when plotting the final model I get a classification tree that seems fairly simple (6 variables shown in tree). However, when I request the final variables from ...
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1answer
16 views

Cutoffs to consider for survival tree

In an tree based algorithm a criterion is measured at certain cutoffs for the variable. This cutoffs are the candidate split points for that variable. How does one come up with candidate split points ...
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95 views

Machine Learning Methods for Binary Classification

I was hoping to get a nice list of alternatives to logistic regression and decision trees for binary classification ("Yes vs. No" or "Cured vs. Not cured"). I am more interested in identifying the ...
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Performance of Decision tree and Association rule mining with increasing size of training data

I planning to do misconfiguration identification using some available dataset. So I have two dataset, one with enough number of observations, say from 1000 to 3000 and another one with less than 50 ...
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67 views

How to Balance my Dataset?

I have 90% negative examples and 10% positive examples,(13,000 observations, 90 Variables). my model shows me that the miss classifications error is 0.1 but my confusion matrix shows me that the TP ...
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68 views

Timeseries Regression - threshold value, regular and time-series covariates

i am trying to find a time-series regression or machine learning package that allows the following analysis: Lets assume that ice-cream sales are a function of: a) a threshold value on outside ...
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61 views

Will decision trees perform splitting of nodes by converting categorical values to numerical in practice?

In Decision trees, while doing classification or regression, are we using only numerical values. Suppose if i am having a column of 'Wind' as a feature. Suppose, I am having 5 rows ( observations ). ...
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65 views

Hierarchical clustering with agnes - how to cut the tree?

I am working on a data.frame with both categorical and metric variables ...
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1answer
43 views

Choosing right range for data while using scikit-learn

I have a dataset with 1175 examples and 21 features which are in the range of [-1, +1], and two class labels 1 and 0. As I read in the most of the resources, it is good to have data in the range of ...
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1answer
45 views

Using SMOTE for building CART models

Suppose I want to build an interpretable model and the response variable is 0/1. However, there are 99% 1's and 1% 0's. The date looks like this: ...
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35 views

How to deal with highly unbalanced data

I want to build a CART on data where the response variable is a binary variable, but it is highly imbalanced(i.e. 100,000 0's and 4000 1's). Are there any R packages that allow you to build CART ...
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1answer
90 views

Random forest and model predictions

I have a working random forest model (classification tree) in R that I made with a training dataset. I used the predict function with a verification dataset: ...
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36 views

RMSE and Decision Trees

I'm running a series of regressions using decision trees and am getting good results, but I've got a question. In the pacakge rpart, you can run cpplot to get a graphical representation of where to ...
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39 views

Decision Trees disadvantage : Inability to examine more than one attribute at a time

I'm reading up on decision trees and in Negnevitsky (2002), one significant limitation on the decision tree is their inability to examine more than one variable at a time. I've been trying to ...
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44 views

Classification trees: the best Predictor and the ability to predict

The topmost decision node, the root node in a classification tree is said to be the best predictor of the model. Does this mean the root node variable is also the best in predicting the target ...
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Transforming nominal attribute to binary for CART

I found the following description regarding model trees for numeric prediction, in which nominal attributes are transformed to binary attributes. Before constructing a model tree, all nominal ...
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32 views

Tree analysis - CHAID cart

I am new to CHAID and want to know how to decide which independent variables I should select to run CHAID Analyis? Is there a technique to select and then apply them and run the analysis? Please guide ...
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105 views

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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24 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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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 ...
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1answer
56 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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“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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59 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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74 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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33 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
49 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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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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30 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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32 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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29 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
83 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 ...
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1answer
30 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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24 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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60 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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121 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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26 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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24 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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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 ...