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

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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
21 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 'chickwts': ...
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8 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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10 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
40 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
16 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 ...
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26 views

Decision tree with adaboost

Helllo! I'm currently learning the AdaBoost algorithm to use it with Decision Tree. I want to implement everything myself (that's the way I learn - implement everything from scratch and later use ...
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1answer
16 views

Using a set as a feature in decision tree classification

I'm faced with a data set where one of the features is a set of 4-5 categories (this number of categories isn't constant). I need to use this feature for building a decision tree. I searched online ...
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2answers
66 views

Is it possible to use SD instead of entropy?

While discussing about decision trees in class, my teacher touched upon the topic of entropy. I have understood the purpose of entropy (have not understood how the formula $H(X)= -\sum_{i}{p(x_i) \log ...
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54 views

What statistical software does NOT provide for Classification and Regression models [closed]

Appended is a list (as far as I can tell) of statistical software that DOES provide for use of Classification and Regression Tree (CART) models. Some have the CART as a trivial case of things like ...
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51 views

Classification problem-Big Data and simple decision rules: logit regression, LDA, random forest, cond. trees, or something else?

This is a big data question from someone who is more accustomed to small data. I would like to develop some classification "rules of thumb," that is, some simple decision rules or a decision tree ...
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8 views

Finding the most relevant predictors (features) to build predictive model

I am building a predictive model using CART. I use features (X1,X2, .. X20) and Y as a target. How can I decide which are the most relevant predictors (filtering correlated and features with less ...
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29 views

Why to use Chi2 instead of accuracy in a decision tree?

Why many decision trees are using Chi2 or Information Gain Ratio to split the node when they can directly use accuracy, lift or AUC?
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50 views

Is Uplift Modeling a solution to Multiple Comparisons problem?

If you want to identify a particular user segment for whom an experiment produced some lift or incremental effect over the control treatment, wouldn’t it be more direct to do uplift modeling? Uplift ...
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1answer
42 views

Chi-Squared significance test for stopping criteria in decision tree

Going through the paper of BFTree(Best First Decision Tree) from (Haijian Shi (2007). Best-first decision tree learning. Hamilton, NZ). I read for pre-pruning do a local attribute selection. And the ...
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1answer
104 views

Questions about decision trees

I'm analyzing decision trees on a regression problem with 12 attributes, a class attribute that can have values between 1-10, and 6497 records. Here is the data. I am using 10 fold cross-validation ...
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1answer
77 views

How can I plot this graph in R? [closed]

I'm reading "An Introduction to Statistical Learning" and noticed the following plot made in the book for a regression tree: I'm trying to make a similar plot for my dataset but can't figure out ...
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1answer
20 views

sklearn.tree.export_graphviz values do not add up to samples

When I run tree.export_graphviz() after training a sklearn.ensemble.RandomForestClassifier() on my data, I get some leaf nodes where the samples count doesn't match the value array, like this: ...
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1answer
25 views

When to use Gini impurity and when to use information gain?

Can someone please explain to me when to use Gini impurity and information gain for decision trees? Can you give me situations/examples of when is best to use which?
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15 views

Regarding post pruning in decision tree

Just 2 issues: 1) what should we do say for example we get 5 Yes and 2 No for a single final leaf node attribute? 2) How to post prune using Chi square test?
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27 views

Iterative Dichotomiser 3 (ID3) decision tree analysis for a small sample size

I am preparing a project which lacks sample size. The data set has only 51 observations. There are 7 predictor variables and the outcome is a dichotomous variable (Yes/No). I am applying ID3 for ...
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26 views

How to Force Split Decision Tree in R

Is there any ways that a user can force split the decision tree in R ? I just think when building decision tree, we may need expert judgement in order to obtain the final model. As far as I know, ...
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1answer
27 views

How can I read this decision tree

I'm sorry, I'm trying to learn some statistics in order to help someone I care about. Here's my problem, I have this decision tree below, for which I have no documentation to help. I cannot find out ...
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22 views

Decision Tree Modelling

Can anyone explain me about Decision tree parameters - minSplit, minBucket, Complexity, minDepth with some simple decision tree example? And how this parameters will affect the accuracy measure? ...
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13 views

Plotting Classification Tree with a lot of Factors - Legend Option?

I want to plot a classification tree and display it nicely. The problem is, because my factor variable has a lot of levels, the node displayed would look something like this: State Name = alabama, ...
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1answer
26 views

Interpret the (visual) length of the branch in decision tree?

I'm using the tree package in R to produce the following tree. The (visual) length of the first split is huge, and I wonder if this signifies something? Perhaps how ...
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21 views

What is “fitted function” in the context of boosted regression tree?

I'm following the tutorial of package dismo's boosted regression tree, which produces two graphs, about fitted function and ...
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1answer
17 views

The Strength of the Decision in Decision Tree

I learn how to use decision tree in R library(rpart) fit <- rpart(Kyphosis ~ Age + Number + Start, data = kyphosis) asRules(fit) return, ...
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1answer
44 views

Posterior probabilities with decision trees or decision forests

Is there a way to get posterior probabilities $P(C | \vec{x})$ (probability that a data item $\vec{x}$ belong to one of the given classes) in a multiclass classification problem using decision trees ...
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14 views

DecisionTreeClassifier scikit-learn : knowing the leaf to which an example belongs to

I am currently reading this paper http://quinonero.net/Publications/predicting-clicks-facebook.pdf , where they are using trees to generate feature that are afterwards fed to a linear classifier. My ...
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1answer
39 views

Visualize difference between 2 classifiers

I trained 2 binary classifiers with the same data (a Decision Tree and a Random Forest). They both made a prediction on the same test data. Now, I want to visualize the difference in classification ...
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6 views

Relative magnitudes of mean squared errors in cross-validation and test data for large regression trees

When pruning a regression tree using cost-complexity pruning, is there any reason to expect that the mean squared errors for the cross-validated data is larger than the mean squared errors for the ...
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20 views

fragmentation problem in decision tree

I am taking a NLP class, in which it says decision tree has the fragmentation problem. It says ...
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27 views
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1answer
36 views

Number of variables for decision trees

I have a data with just 5 independent variables and a response. I am dealing with a classification problem. Will decision trees perform well or the number of variables have to be higher to get ...
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6 views

Decision Tree In Power System Implementation

I am completely new in Machine Learning and very interested to be familiar with its nice approaches which would help me in assessing the behavior of any system. At the moment I am going to focus on DT ...
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56 views

Using an RMSE with derived confidence interval, to generate a prediction interval for an estimate

Previous questions have asked about creating prediction intervals for estimates derived from random forests or boosted regression trees, in a similar way to is easily achieved with linear regression ...
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34 views

cost matrix, unbalanced class, oversampling and threshold probability

Let's suppose I have a cost matrix with TP=+90 FP=-10 TN=0 and FN=-10, and that the class is unbalanced. I need to capture the costs in my decision. To do so, I always consider the probability ...
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1answer
29 views

What is the intuition behind the Kappa statistical value in classification

I understand the formula behind the Kappa statistic value and how to calculate the O and E value from a confusion matrix. My question is what is the intuition behind this measure? Why does it work so ...
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12 views

Need Insight on Measuring Variable Effect

I apoligize in advance for the wall of text. I'm working on a project in which I have been asked to determine what factors influence employees leaving our company. Also, it would be useful to be able ...
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13 views

Why does the regression model tree consider only those parameters along the path for the model?

When we try to model a regression tree by the M5 approach, while building the model at a particular leaf node, we consider only those variables that have been on the path from the root node to this ...
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38 views

What is the difference between the M5 regression model tree and the Cubist method for regression?

I am aware of how the M5 regression model trees work. I know that they fit linear regression models at every leaf of the regression tree and that every parent in the node is also associated with a ...
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23 views

Sampling on dependent variable appropriate for building decision tree for rare event data?

In order to detect significant interaction terms prior to building a logistic regression model, I'm first running a simple decision tree on my data using the rpart package in R. I'm predicting a ...
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21 views

using SAS for decision tree

I am quite new to SAS. I wanted to figure out how we can use Test dataset and Train dataset seperately. As of now i was dividing the existing dataset into Training and Test dataset. My requirement is ...
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41 views

How does rpart in R differ from SPSS classification trees?

I am using rpart in R for some decision trees. I decided to check the results in SPSS - classification - trees, and different variables were selected. In rpart, I'm using method="class" and the ...
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1answer
113 views

Interpreting rpart output for decision trees?

How do I go about selecting the ideal location to use for pruning the tree here? Or maybe someone can explain to me in simple language what this output means. I see that rel_error is constantly ...
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2answers
114 views

How can I get more precise regression tree?

I am a complete newbie to regression trees so maybe I am not understanding it properly. I got the following tree from my analysis (function tree() from R package ...
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74 views

Interpreting output from cvFit(), understanding cross-validation in classification tree model

I am trying to understand how to interpret the output for cvFit(). The data is from UCI's ML repository. This is my model ...
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0answers
15 views

Degrees of freedom when splitting populations

I have a question relating to degrees of freedom when I have a number parameters in a model for a population, and then I want to split the population. Say for a certain population I have a the ...
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1answer
31 views

Suitable function to choose the best split in a regression tree/oblivious tree

My main objective is to construct a regression (decision) tree. It is a part of a boosting algorithm using additive regression trees. The first question is what other functions (other than least ...