Tagged Questions

0
votes
0answers
58 views

Interpreting output of 10-fold CV on classification tree

Using info from Decision tree model evaluation for "training set " vs "testing set " in R , I was able to run a 10-fold cross validation on my entire dataset, using this command: ...
0
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0answers
66 views

MS business intelligence development studio CART analysis

I'm doing some clinical database research and in an effort to lessen the burden on our statistical staff, I started to look for different software solutions to get the analyses I need, and that's ...
0
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0answers
54 views

Variables selection (continuous and classification): how to do in R?

My dataset have both classification (categorical) and continuous variables, ~ 300 variables in all. I'm looking for a way to reduce my attributes to be less than 300 and put them in the decision tree ...
1
vote
0answers
56 views

Deciding attributes for decision trees

I'm a complete beginner when it comes to R and decision trees, but I was asked to take a look at this to see if this was a viable solution for my data. So please excuse me if I say completely wrong. ...
0
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0answers
73 views

Model Trees: M5, Cubist - What about the assumptions of the linear models being used?

From what I understood, these models differ from CARTs for regression, mostly because they fit a linear model at the leaves of the tree instead of simply taking an average. They also "smooth" the tree ...
0
votes
1answer
283 views

Decision tree model evaluation for “training set ” vs “testing set ” in R

So I got my training set with 70% of my data called "train" / 30% "test" I use ctree to get my decision tree model with something like this code below : ...
1
vote
1answer
166 views

mobForest R Package

I have recently begún to learn about model based recursive partitioning by playing around with MOB in the party package. I came across this mobForest package but am a little baffled towards what it is ...
0
votes
1answer
183 views

Predict sales levels with decision trees

I need to build a model using climate variables (temperature, rainfall) to predict monthly sales (horizon of 6 months) for certain product. The data has strong seasonality and a standard regression ...
2
votes
1answer
157 views

Interaction depth parameter in GBM

In the GBM package one is supposed to be able to provide interaction.depth>2, which means higher-order interactions between features. However, the resulting trees (as seen by pretty.gbm.tree) never ...
1
vote
1answer
205 views

how to interpret reading decision tree result from ctree() in r?

After running ctree(model) My result look like this below : ...
0
votes
1answer
116 views

Error while calculating metrics like AUC, ACC in R

I am trying to make predictions on my validation data using a decision tree model created with training data set. I am able to do that with success but, I am not able to calculate various metrics like ...
2
votes
0answers
689 views

Interpreting decision trees outputs in R?

I have created 2 decision trees, I just want to assure if I am making correct interpretation about it. Here is my first tree: Note: Right click on image and select view image to view it clearly! ...
2
votes
3answers
302 views

Which type of regression fits better?

I am a newbie in data mining world. I have a general question. I have a data set which has 10 independent variables and one target variable named as category which has 9 values like: 1, 2, 3, 4, 5, 6, ...
1
vote
0answers
64 views

Growing a classification tree manually

I want to create some CARTs in R. I used Clementine a while ago for this purpose and remember I could go into "manual mode" and grow the trees by hand. I could manually choose which variable to use ...
8
votes
1answer
2k views

How to actually plot a sample tree from randomForest::getTree()?

Anyone got library or code suggestions on how to actually plot a couple of sample trees from: getTree(rfobj, k, labelVar=TRUE) (Yes I know you're not supposed ...
5
votes
0answers
367 views

Choosing complexity parameter in CART

In the rpart() routine to create CART models, you specify the complexity parameter to which you want to prune your tree. I have seen two different recommendations for choosing the complexity ...
2
votes
0answers
112 views

Is it possible to have xerror increased in a tree using rpart?

I am new to R and rpart package. When I plot the tree using rpart: ...
2
votes
2answers
192 views

Is it possible to build a more “controllable” decision tree like below?

I have 2 real and 1 discrete input variable whereas the output variable takes either of the 2 nominal values (i.e. 2 class problem). First I used Weka to train C 4.5 decision tree in a 10-fold cross ...
1
vote
0answers
270 views

How to interpret result from mvpart object in R?

I used R mvpart package to create a multivariate regression tree. This is part of the output: ...
3
votes
1answer
1k views

What are some useful guidelines for GBM parameters?

What are some useful guidelines for testing parameters (i.e. interaction depth, minchild, sample rate, etc.) using GBM? Let's say I have 70-100 features, a population of 200,000 and I intend to test ...
2
votes
0answers
185 views

How to calculate fitted values when using AdaBoost via gbm package in R? What does fitted values mean?

I poseted this question about two weeks ago. But it was closed because I cross-posted here and on SO. So I deleted the post on SO and re-post here. My question is as below. First of all I'm not ...
1
vote
0answers
264 views

How to calculate fitted values when using AdaBoost via gbm package in R? [closed]

First of all I'm not good at English. So please be patient to interpret my words. I really need your help. I used the R package GBM as probably my predictive modeling. I made a model with adaboost ...
0
votes
1answer
127 views

Heading in plots by mvpart()?

How can I put in a heading in the tree output when using mvpart()? I am using xv="1se". e.g. using the spider data in mvpart ...
1
vote
1answer
227 views

Determining regression tree quality

I'm attempting to use the rpart R package, and I'm having difficulty figuring out how to determine the quality of a given tree output. For most linear models I ...
8
votes
2answers
932 views

party vs. rpart vs. ??? for partitioning trees in R

It's been a while since I looked at partitioning trees. Last time I did this sort of thing, I like party in R (created by Hothorn). The idea of conditional inference via sampling makes sense to me. ...
0
votes
1answer
338 views

lift/uplift/netlift modeling: CART analysis maximizing a t-statistic from a multivariate regression

For tree based modeling most packages use some data element as the dependent variable. In uplift modeling the goal is to maximize the difference between treatment and control groups. One way to ...
1
vote
0answers
201 views

Obtaining resampling based estimates of prediction error in boosted regression tree model

I try to use the gbm.fit() function for a boosted regression tree model implemented in the R package gbm. To investigate e.g., the bootstrapped prediction error and ...
4
votes
0answers
142 views

Tree size in gradient tree boosting

Gradient tree boosting as proposed by Friedman uses decision trees with J terminal nodes (=leaves) as base learners. There are a number of ways to grow a tree with ...
2
votes
1answer
223 views

How to collapse ordinal variable values into significant different values?

I have an ordinal variable related to an outcome that is comprised of many levels and I´d like to collapse the number of ordinal values as much as possible. ...
2
votes
1answer
173 views

Linear statistic for measuring association in the party R package

I had asked a general question about conditional inference trees via party a while back and gotten a great reply. I am revisiting this procedure and trying to make sense of the linear statistic that ...
5
votes
3answers
277 views

Classifying IP addresses with a decision tree

I am working on a classification problem using IP addresses as input and I am trying to find which IP addresses or subnets are likely to belong to a spammer. I have data consisting of the four octets ...
5
votes
3answers
247 views

Recursive partitioning using median (instead of mean)

As I am only familiar with the basics regarding decision trees I would like to ask, with the risk of stating silly question: Is it possible to perform recursive partitioning with the group median as ...
1
vote
1answer
428 views

How to choose the number of splits in rpart()?

I have used rpart.control for minsplit=2, and got the following results from rpart() ...
24
votes
1answer
3k views

Conditional inference trees vs traditional decision trees

Can anyone explain the primary differences between conditional inference trees (ctree from party package in R) compared to the ...
3
votes
1answer
448 views

Organizing a classification tree (in rpart) into a set of rules?

Is there a way that once a complex classification tree is constructed using rpart (in R), to organize the decision rules produced for each class? So instead of getting one huge tree, we get a set of ...
6
votes
2answers
379 views

Are there any libraries available for CART-like methods using sparse predictors & responses?

I'm working with some large data sets using the gbm package in R. Both my predictor matrix and my response vector are pretty sparse (i.e. most entries are zero). I was hoping to build decision trees ...
3
votes
1answer
127 views

How to produce a CI for a value predicted in CART?

My goal is to create CI for the CART prediction of new_x Consider the following code: ...
8
votes
3answers
5k views

What is Deviance? (specifically in CART/rpart)

What is "Deviance," how is it calculated, and what are its uses in different fields in statistics? In particular, I'm personally interested in its uses in CART (and its implementation in rpart in R). ...
6
votes
2answers
2k views

How to measure/rank “variable importance” when using CART? (specifically using {rpart} from R)

When building a CART model (specifically classification tree) using rpart (in R), it is often interesting to know what is the importance of the various variables introduced to the model. Thus, my ...
3
votes
1answer
342 views

Estimate the “meaningful” predictors for a value in a CART model (rpart)

When building a CART model (specifically classification tree) using rpart (in R), it is sometimes obvious that there are variables (X's) that are meaningful for predicting some of the outcome (y) ...
3
votes
4answers
765 views

Does rpart use multivariate splits by default?

I know that R's rpart function keeps the data it would need to implement multivariate split, but I don't know if it's actually performing multivariate splits. I've ...
13
votes
5answers
1k views

Alternatives to classification trees, with better predictive (e.g: CV) performance?

I am looking for an alternative to Classification Trees which might yield better predictive power. The data I am dealing with has factors for both the explanatory and the explained variables. I ...
9
votes
2answers
1k views

How does random forest generate the random forest

I am not an expert of random forest but I clearly understand that the key issue with random forest is the (random) tree generation. Can you explain me how the trees are generated? (i.e. What is the ...