similar to: It was a sad day for the Statistics profession

Hi all, There is now a package available on CRAN that provides an R interface to Leo Breiman's random forest classifier. Basically, random forest does the following: 1. Select ntree, the number of trees to grow, and mtry, a number no larger than number of variables. 2. For i = 1 to ntree: 3. Draw a bootstrap sample from the data. Call those not in the bootstrap sample the

Hi all, There is now a package available on CRAN that provides an R interface to Leo Breiman's random forest classifier. Basically, random forest does the following: 1. Select ntree, the number of trees to grow, and mtry, a number no larger than number of variables. 2. For i = 1 to ntree: 3. Draw a bootstrap sample from the data. Call those not in the bootstrap sample 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

Dear all , I would like to use the function randomForest to predict the probability of relocation failure of a GPS collar as a function of several environmental variables x (both factor and numeric: slope, vegetation, etc.) on a given area. The response variable y is thus success (0)/failure(1) of the relocation, and the sampling unit is the pixel of a raster map. My aim is to build a map

Dear Lister, plot() is using the data range as the default limits of yaxis. Is there any way I can change the limits? I just look at the help of plot() and par() and couldn't find answers. Thanks. -- WenSui Liu (http://spaces.msn.com/statcompute/blog) Senior Decision Support Analyst Health Policy and Clinical Effectiveness Cincinnati Children Hospital Medical Center

Hi, I had two questions regarding random forests for regression. 1) I have read the original paper by Breiman as well as a paper dicussing an application of random forests and it appears that the one of the nice features of this technique is good predictive ability. However I have some data with which I have generated a linear model using lm(). I can get an RMS error of 0.43 and an R^2 of

Hi, In R, how to do missing value replacement for test data in randome forest in the way Breiman decribed. thanks in advance iris

I remember in one slide of Prof. Ripley's presentation overhead, he said the most popular data analysis software is excel. So is there any resource or tutorial on this topic? Thank you so much!

A few days ago I asked whether there were options other than na.action=na.fail for the R port of Breiman?s randomForest; the function?s help page did not say anything about other options. I have since discovered that a pdf document called ?The randomForest Package? and made available by Andy Liaw (who made the tool available in R---thank you) does discuss an option. It is an implementation of

Dear Lister, If I have a list of number, say x<-c(0.1, 0.5, 0.6...), how to use a for() to loop through each number in x one by one? Thank you so much! wensui [[alternative HTML version deleted]]

> From: Weiwei Shi > > it works. > thanks, > > but: (just curious) > why i tried previously and i got > > > is.vector(sample.size) > [1] TRUE Because a list is also a vector: > a <- c(list(1), list(2)) > a [[1]] [1] 1 [[2]] [1] 2 > is.vector(a) [1] TRUE > is.numeric(a) [1] FALSE Actually, the way I initialize a list of known length is by

Hi, I'm looking to perform a classification analysis on an imbalanced data set using random Forest and I'd like to reproduce the weighted random forest analysis proposed in the Chen, Liaw & Breiman paper "Using Random Forest to Learn Imbalanced Data"; can I use the R package randomForest to perform such analysis? What is the easiest way to accomplish this task? Thanks,

Dear Lister, I understand merge() can be used to join 2 data frames based on 1 variable. But how about merge based on more than 2 variables? Thank you so much! -- WenSui Liu (http://spaces.msn.com/statcompute/blog) Senior Decision Support Analyst Health Policy and Clinical Effectiveness Cincinnati Children Hospital Medical Center [[alternative HTML version deleted]]

Greetings. I'm trying to determine whether to use rpart or randomForest for a classification tree. Has anybody tested efficacy formally? I've run both and the confusion matrix for rf beats rpart. I've looking at the rf help page and am unable to figure out how to extract the tree. But more than that I'm looking for a more comprehensive user's guide for randomForest including

hi all is there a package that undertakes subset selection but BASED ON AIC or any other information criteria. i've seen the "subselect" and the "leaps" package but i have not played around with them yet. thanx

"classwt" in the current version of the randomForest package doesn't work too well. (It's what was in version 3.x of the original Fortran code by Breiman and Cutler, not the one in the new Fortran code.) I'd advise against using it. "sampsize" and "strata" can be use in conjunction. If "strata" is not specified, the class labels will be used.

Dear Listers, I have 2 questions regarding xml. 1) how to read/write tables in xml? 2) compared with csv, is xml a better way to transfer data cross systems/applications? Thank you so much for your insight. -- WenSui Liu (http://statcompute.blogspot.com) Senior Decision Support Analyst Health Policy and Clinical Effectiveness Cincinnati Children Hospital Medical Center [[alternative HTML

I'm afraid I have to retire from being a maintainer of some apps for a while. I need to put Windows back on my box and will not have the option for a dual boot or even a linux boot for a while. Hopefully this will change in the future, I've already removed my name as maintainer of any games I can remember I was listed against. It is truly a sad day for me and if I had any other option I

Hallo! I am a student of the Politecnico di Milano (Milan, italy) and I'm working on CARTs. I'm trying to use the R rpart function with a personalized splitfunction... but I'm not able to do it! More precisely, I would like to know what is the meaning of the function 'init', 'split' and 'eval' named in the help page.I can't find any answer in

Dear R, Short verse of the question: Is there R code which will calculate surrogate splits and/or delta impurity for decision trees at each node? Long Version: I have local, legacy code which I use to calculate my decision trees. I would like to switch to R, but as I understand it surrogate splits are not implemented. Surrogate splits and feature ranking are described in Breiman et al