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

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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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35 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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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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42 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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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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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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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
19 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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15 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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235 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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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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12 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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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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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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25 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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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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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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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
44 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
49 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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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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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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43 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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30 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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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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26 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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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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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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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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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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30 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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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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61 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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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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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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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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39 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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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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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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49 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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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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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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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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35 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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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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21 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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51 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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23 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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51 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 ...