similar to: An Appreciation of Leo Breiman (1928-2005)

Apologies for cross posting.... Early-Bird Registration Discount Deadline Just a quick reminder. If you are interested in attending CART Data Mining 2004 (San Francisco), the EARLY-BIRD discounted registration deadline is January 30th, 2004. Registration materials are available at: http://www.cartdatamining.com/RegCART04.pdf Other deadlines: Paper Submission: January 12th Student Contest:

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

Apologies for cross posting CART Data Mining 2004, San Francisco, March 22-24, 2004 Below are links for the registration and the latest scheduling information. Please note that you can register with an early-bird discount if you register NOW and write the words "SCHEDULE" on your registration form. Homepage: http://www.cartdatamining.com Detailed Conference Schedule:

DATA MINING 2006 CONFERENCE sponsored by Salford Systems San Diego, California: March 30 - March 31, 2006 (with a Welcome Reception on March 29th at 6PM) Two Full Days of Real-World Case Study Presentations Schedule: www.salforddatamining.com/docs/schedule06.pdf <http://www.salforddatamining.com/docs/schedule06.pdf> *Conference Highlights:* * State-of-the-Art Research from Leading

Apologies for cross posting.... ----------------------------------------------------------------------------- Salford Systems Data Mining 2005 Second International Data Mining Conferences Focusing on the Contributions of Data Mining to Solving Real World Challenges Honoring the Real-World Experiences of Data Mining Visionaries Leo

DATA MINING 2006 CONFERENCE sponsored by Salford Systems San Diego, California: March 29 - March 31, 2006 The Conference will offer Real-World Case Study Presentations including Cutting Edge Topics: Crime Prevention * Anti-Terrorism * Gambling * Sports * Video Games * Food & Water Science * Diet Research * Standardized Testing There will be special courses available for attendees who are

Last chance to register for Sydney, Australia Data Mining Training and Workshop. Training: June 5-7, 2006 Workshop: June 8, 2006 Register for 1, 2, 3 or 4 days. Location: Australian Graduate School of Management, Lecture Theatre Number 1 O'Connell Street Sydney, Australia Objective: The training and workshop are aimed at bringing together researchers and practitioners to learn about data

Salford Data Mining Conference August 23rd - 25th, 2009 San Diego, California Early-Bird Registration Deadline: July 24th, 2009 http://SalfordDataMining.com/agenda.php Post-Conference Training August 26th - 28th, 2009 Our conference will offer prominent keynote speakers and informative real world application solutions. Conference topics include: * What Data Mining Has to Say About the

Dear R users, I've just released a new version of randomForest (available on CRAN now). This version contained quite a number of new features and bug fixes, compared to version prior to 4.0-x (and few more since 4.0-1). For those not familiar with randomForest, it's an ensemble classifier/regression tool. Please see http://www.math.usu.edu/~adele/forests/ for more detailed information,

Dear R users, I've just released a new version of randomForest (available on CRAN now). This version contained quite a number of new features and bug fixes, compared to version prior to 4.0-x (and few more since 4.0-1). For those not familiar with randomForest, it's an ensemble classifier/regression tool. Please see http://www.math.usu.edu/~adele/forests/ for more detailed information,

A new version of the randomForest package is now available on CRAN. The DESCRIPTION is: Package: randomForest Title: Breiman's random forest for classification and regression Version: 3.4-1 Depends: R (>= 1.5.0) Author: Fortran original by Leo Breiman and Adele Cutler, R port by Andy Liaw and Matthew Wiener. Description: Classification and regression based on a forest of trees using

Our CEO, Dr. Dan Steinberg, is planning to visit Europe in May. He would like the opportunity to introduce statisticians (and statistically minded people) to data mining, data mining applications and to forefront data mining tools. Our algorithms are probably familiar to many statisticians (CART, MARS, MART, TreeNet and RandomForests), although it isn't necessary to be a statistician to

I was under the impression that the tree method (e.g. as implemented in rpart) was insensitive to monotonic transformations of the dependent variable. e.g. Breiman Olshen et al. Classification and Regression Trees state "In a standard data structure [a tree] is invariant under all monotone transformations of individual ordered varaibles" (p. 57) However, I get very different results

I'm interested in further understanding the differences in using many classification trees to improve classification rates. I'm also interested in finding out what I can do in R and which methods will allow prediction. Can anybody point me to a citation or discussion? Specifically, I want to classify remotely sensed imagery where training data is extracted on class membership by the user.

--- 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,

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

Our CEO, Dr. Dan Steinberg, is planning to visit Germany in September. He would like the opportunity to introduce statisticians (and statistically minded people) to data mining, data mining applications and to forefront data mining tools. Our algorithms are probably familiar to many statisticians (CART, MARS and MART), although it isn't necessary to be a statistician to use our tools. We

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

Full_Name: Adam B. Olshen Version: 1.3.1 OS: Linux Submission from: (NULL) (140.163.222.233) There appears to be a bug with write.table if the object being written is a matrix. Specifically, the option row.names=F gives an error. I have seen this problem repeated in the Windows implementation. An example is below. Adam Olshen olshena@mskcc.org This works: >