similar to: Difference between "tree" and "rpart"

Hi, I am using rpart decision trees to analyze customer churn. I am finding that the decision trees created are not effective because they are not able to recognize factors that influence churn. I have created an example situation below. What do I need to do to for rpart to build a tree with the variable experience? My guess is that this would happen if rpart used the loss matrix while creating

Hi, When I look at the summary of an rpart object run on my data, I get 7 nodes but when I plot the rpart object, I get only 3 nodes. Should the number of nodes not match in the results of the 2 functions (summary and plot) or it is not always the same? Look forward to your reply, Carol -------------------------------------------- ?summary(rpart.res) Call: rpart(formula = mydata$class ~ ., data

--- included message ---- Thus, my question is: *What common measures exists for ranking/measuring variable importance of participating variables in a CART model? And how can this be computed using R (for example, when using the rpart package)* ---end ---- Consider the following printout from rpart summary(rpart(time ~ age + ph.ecog + pat.karno, data=lung)) Node number 1: 228 observations,

I noticed I got a strange connection from what seems to be a user in italy?!? and he connected to my SMB client maybe?? I'm assuming the errors in his logfile ( http://68.48.247.187/log.gustavo.txt ) not finding the service.c file are because he is being denied access.. but how is he connecting in the first place.. And why isnt he being refused by my servers hosts.deny file...? I have

Hi, I am using rpart as a part of my masters' project. I am trying to print out the resulting model using plot() function along with text() function. I am having difficulties with labels being cut-off. In text() function, I am using use.n=T option to get the number of people in each nodes but the on the lower and left part of the plot, the numbers get cut off. Thanks! Linus [[alternative

Running on an Alpha machine which reports (uname -a) OSF1 bsdx01.bs.ehu.es V4.0 878 alpha and using the binary distribution put together by Albrecht Gebhardt (in http://cran.at.r-project.org/bin/osf/osf4.0/tar/alpha_ev5/) I obtain core dumps whenever I try to use package rpart. I have R REMOVE'd the rpart package, downloaded the source rpart_1.0-7.tar from CRAN and

Hi all: I see a lot of the errors below in /var/log/messages on my firewall: Aug 1 00:47:44 munin kernel: [109008.257109] martian source 192.168.1.5 from 127.0.0.1, on dev eth1 Aug 1 00:48:44 munin kernel: [109068.257384] martian source 192.168.1.5 from 127.0.0.1, on dev eth1 Aug 1 00:49:44 munin kernel: [109128.257509] martian source 192.168.1.5 from 127.0.0.1, on dev eth1 Aug 1 00:50:44

Hi, all Our understanding of how classification trees in Rpart treat missing is that if the variable is ordinal(continous), Rpart, by default, imputes a value for missing. How do we do the classification tree and tell Rpart not to impute. That is, what command is used to turn off the imputation. Also, if we do get true missing, how does classification tree analysis in Rpart treat missing when

Guys, good afternoon I'm using in my bond interfaces as active backup, in theory, should assume an interface (or work) only when another interface is down. But I'm just lost packets on the interface that is not being used and is generating packet loss on bond. What can that be? Follow my settings bond [root at xxxxx ~]# ifconfig bond0 ; ifconfig eth0 ; ifconfig eth1 bond0

Hi all, I am trying to play around with the randomForest function for classification. I know its performance is great. I am currently using the default options. It has many options. How do I further tweak the options so that I can make its performance even better? What are the options that are mostly used? Thanks a lot! M [[alternative HTML version deleted]]

Greetings, I checked the Indian diabetes data again and get one tree for the data with reordered columns and another tree for the original data. I compared these two trees, the split points for these two trees are exactly the same but the fitted classes are not the same for some cases. And the misclassification errors are different too. I know how CART deal with ties --- even we are using the

We are trying to make a decision tree using rpart and we are continually running into the following error: > fit_rpart=rpart(ENROLL_YN~MINORITY,method="class") > summary(fit_rpart) Call: rpart(formula = ENROLL_YN ~ MINORITY, method = "class") n= 5725 CP nsplit rel error 1 0 0 1 Error in yval[, 1] : incorrect number of dimensions ENROLL_YN is a

[ sorry for cross-posting this to newbies and users, but I''m a bit desperate to get this resolved ] This is strange... I had this working before without any problems, and recently we started to have some odd issues. I can''t be sure exactly what has changed as I''m unfortunately not the only person with access to the server. {sigh} The problem is that I pretty much

Dear R users, I’m trying to understand how correlated predictors impact the Relative Importance measure in Stochastic Boosting Trees (J. Friedman). As Friedman described “ …with single decision trees (referring to Brieman’s CART algorithm), the relative importance measure is augmented by a strategy involving surrogate splits intended to uncover the masking of influential variables by others

Hi, I have a setup problem with Shorewall 4.0.6, which I can''t figure out why it is not working: I want to install a fireall with 2 extra interfaces : - My serv ("dmz") zone is a /28 subnet behind eth1, with a small number of SUN servers (IPs between ABC.DEF.75.1 and .13), one of which is a DHCP server for the 75 subnet. - The loc zone are PCs in the 75 subnet behind eth2

Hi I''m trying to monitor my multi ISP shorewall with swping, the script works fine, i can see in log when an ISP is down, the script restart shorewall and /etc/shorewall/isusable is called, however in the swping log after the shorewall restart i see again a route by ISP (even the ISP down), is it normal ? should i not see one route less? shorewall version 4.4.5.4-1. ****

Hello there. I have fitted a rpart model. > rpartModel <- rpart(y~., data=data.frame(y=y,x=x),method="class", ....) and can use rpart$where to find out the terminal nodes that each observations belongs. Now, I have a set of new data and used predict.rpart which seems to give only the predicted value with no information similar to rpart$where. May I know how

Dear R users, I'm working with the rpart package and want to evaluate the performance of user defined split functions. I have some problems in understanding the meaning of the xval argument in the two functions rpart.control and xpred.rpart. In the former it is defined as the number of cross-validations while in the latter it is defined as the number of cross-validation groups. If I am

Dear R people, I was recently reading the book `Classification and Regression Trees' by Breiman. This book talks about the CART program. Both Splus and R have implementations of this. However, the book talks about the possibility of extending the existing `standard' set of questions (for continuous variables, these are of the form X < c where X is the variable, c some const) to

We are seeing the following in our logs: Nov 25 16:21:41 fw kernel: martian source 139.142.66.253 from 10.0.0.199, on dev eth0 Nov 25 16:21:41 fw kernel: ll header: 00:a0:c9:60:0e:b2:00:02:7e:21:0e:dc:08:00 00:a0:c9:60:0e:b2 is the mac of our firewall interface on IP 139.142.66.253. 00:02:7e:21:0e:dc is the mac of our Cisco router on IP 10.0.0.1 10.0.0.199 is a Cisco switch - we have about