similar to: Recursive partitioning algorithms in R vs. alia

Hi: For those of you who are adept at both SAS and R, I have the following questions: a) What are some reasons / tasks for which you would use R over SAS and vice versa? b) What are some things for which R is a must have that SAS cannot fulfill the requirements? I am on the ramp up on both of them. The general feeling that I am getting by following this group is that R updates to the product are

Hi All, I am trying to learn Neural Networks. I found that R has packages which can help build Neural Nets - the popular one being AMORE package. Is there any book / resource available which guides us in this subject using the AMORE package? Any help will be much appreciated. Thanks, Indrajit

I want to create a neural network, and then everytime it receives new data, instead of creating a new nnet, i want to use a backpropagation algorithm to adjust the weights in the already created nn. I'm using nnet package, I know that nn$wts gives the weights, but I cant find out which weights belong to which conections so I could implement the backpropagation algorithm myself. But if anyone

Hello, I would like to test some learning algorithms (C5.0, or C4.5) using decision trees or neural network. I didn't find anything in the R documentation for functions to apply on datasets (well, English is not my mother tongue and I have some problems to understand some functions descriptions). Does anybody know where I can find anything about that ? Thank you very much, Thomas

Hi, I use nnet for my classification problem and have a problem concerning the calculation of the final value for my validation data.(nnet only calculates the final value for the training data). I made my own final value formula (for the training data I get the same value as nnet): # prob-matrix pmatrix <- cat*fittedValues tmp <- rowSums(pmatrix) # -log likelihood

According to Dr. Breiman, the RF should be more accurate method than a single tree. However, the performance of each method seems to depend on the proprotion of outcome variable in my case. My data set is a typical classification problem (predict bad guys). When I ran both of them with different proportion of outcome variables(there's a criterion to measure the degree of bad behavior), I

Hi there, Sorry for the double email. Does R have the packages for the following clustering methods? And if it does, what the commands for them? 1. SOM (Self-organization map) 2. Graph partitioning: 3. Neural network 4. Probability Binning Thank you very much! Linda [[alternative HTML version deleted]]

Hi there, I am growing classification trees using the 'tree' package add-on to R. I would like to convert the 'R' output to the SAS format used by Salford Systems' commercial CART software in order to interface with some other software. My question is: How can I parse the R tree data structure in order to infer the tree structure? The 'tree' class has a member

Hi, Being a novice this is my first usage of R. I am trying to use rpart for building a decision tree in R. And I have the following dataframe Outlook Temp Humidity Windy Class Sunny 75 70 Yes Play Sunny 80 90 Yes Don't Play Sunny 85 85 No Don't Play Sunny 72 95 No Don't Play Sunny 69 70 No Play Overcast 72 90 Yes Play Overcast 83 78 No Play Overcast 64 65 Yes Play Overcast 81 75

Readers, Using version 251 I tried the following command: lm(y~a+b,data=datafile) Resulting in, inter alia: ... coefficients (intercept) a 1.2 3.4 Packages installed: acepack ace() and avas() for selecting regression transformations adlift An adaptive lifting scheme algorithm akima Interpolation of irregularly spaced

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

I am trying to make a decision tree using rpart. The function runs very quickly considering the size of the data (1742, 163). When I call the summary command I get this: > summary(bookings.cart) Call: rpart(formula = totalRev ~ ., data = bookings, method = "class") n=1741 (1 observation deleted due to missingness) CP nsplit rel error 1 0 0 1 Error in yval[, 1] :

Hi, I am trying to read a SAS version 9.1.3 SAS dataset into R (to preserve the SAS labels), but am unable to do so (I have read in a CSV version). I first created a transport file using the SAS code: libname ces2 'D:\CES Analysis\Data'; filename transp 'D:\CES Analysis\Data\fadata.xpt'; /* create a transport file - R cannot read file created by proc cport */ proc

Dear useRs: I try to plot an rpart object but cannot get a nice tree structure plot. I am using plot.rpart and text.rpart (please see below) but the branches that connect the nodes overlap the text in the ellipses and rectangles. Is there a way to get a clean nice tree plot (as in the Rpart Mayo report)? I work under Windows and use R2.11.1 with rpart version 3.1-46. Thank you. Tudor ...

Hi everyone, Could somebody explain to me what is the package/function for classification analysis. I am performing analysis of music files in the form of MIDI files. I end up with about 750 dependent variables from the analysis, I also have a number of independent/grouping variables that I set manually. What I would like is to be able to predict which group a particular MIDI files belongs to

Can I say that RPART is a modified algo of CART and PARTY a modified of CHAID? Thanks. ---- Chua Siang Li Consultant - Operations Research Acceval Pte Ltd Tel: 6297 8740 Email: siang.li.chua at acceval-intl.com Website: www.acceval-intl.com This message and any attachments (the "message"...{{dropped:12}}

I've been using the package rpart with R 1.3.0 for Windows to produce simple classification trees for some measurement data from paleontological specimens. Both the rpart documentation and the output confirm that the program produces splits on continuous data that leave "holes" in the data. It is probably of little practical importance, but is there a reason why the binary

Hello all, When building a CART model (specifically classification tree) using rpart, it is sometimes interesting to know what is the importance of the various variables introduced to the model. 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

Apologies for cross posting.... --------------------------------------------------------------------- CART Data Mining'04: First International CART(R) Conferences Focusing on the Data Mining technology of Leo Breiman, Jerome Friedman, Richard Olshen, Charles Stone (CART, MARS(R), TreeNet(tm), PRIM(tm)...) First Call For submissions

I am one of only 5 or 6 people in my organization making the effort to include R/Splus as an analysis tool in everyday work - the rest of my colleagues use SAS exclusively. Today, one of them made the assertion that he believes the numerical algorithms in SAS are superior to those in Splus and R -- ie, optimization routines are faster in SAS, the SAS Institute has teams of excellent numerical