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HI, Dear Greg, I AM A NEW to GBM package. Can boosting decision tree be implemented in 'gbm' package? Or 'gbm' can only be used for regression? IF can, DO I need to combine the rpart and gbm command? Thanks so much! -- Sincerely, Changbin -- [[alternative HTML version deleted]]

Hi, Dear Greg, Sorry to bother you again. I have several questions about the 'gbm' package. if the train.fraction is less than 1 (ie. 0.5) , then the* first* 50% will be used to fit the model, the other 50% can be used to estimate the performance. if bag.fraction is 0.5, then gbm use the* random* 50% of the data to fit the model, and the other 50% data is used to estimate the

Anyone know if/how you can use the new wisotool (http://wiki.winehq.org/wisotool) with the games it supports through Steam? I have several of the titles it "supports" and would love to give it a try if it works through Steam. Regards, ~Jeff

...rsity Ph: (410) 502-2619 Fax: (410) 614-9625 Email: rvaradhan at jhmi.edu Webpage: http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html ------------------------------------------------------------------------ ---- -------- -----Original Message----- From: Ridgeway, Greg [mailto:gregr at rand.org] Sent: Monday, September 18, 2006 2:17 PM To: r-help at stat.math.ethz.ch Cc: Ravi Varadhan Subject: Re: [R] LARS for generalized linear models Check out Park & Hastie's glmpath package. They have a really clever analysis and implementation of a generalized least angle regres...

When compiling samba-3.0.7 on Redhat-7.2, stock kernel 2.4.26, I get undefined references: ------- Compiling libads/ads_status.c with -fPIC Linking nsswitch/libnss_wins.so lib/system.po: In function `sys_dlopen': lib/system.po(.text+0xc17): undefined reference to `dlopen' lib/system.po: In function `sys_dlsym': lib/system.po(.text+0xc3b): undefined reference to `dlsym'

Generalized Boosted Models (gbm) This package implements extensions to Y. Freund and R. Schapire's AdaBoost algorithm and J. Friedman's gradient boosting machine (aka multivariate adaptive regression trees, MART). It includes regression methods for least squares, absolute loss, logistic, Poisson, Cox proportional hazards/partial likelihood, and the AdaBoost exponential loss. It handles

Generalized Boosted Models (gbm) This package implements extensions to Y. Freund and R. Schapire's AdaBoost algorithm and J. Friedman's gradient boosting machine (aka multivariate adaptive regression trees, MART). It includes regression methods for least squares, absolute loss, logistic, Poisson, Cox proportional hazards/partial likelihood, and the AdaBoost exponential loss. It handles

The Toolkit for Weighting and Analysis of Nonequivalent Groups (twang 1.0) has been released to CRAN. The package collects functions useful for computing propensity score weights for treatment effect estimation, developing nonresponse weights, and diagnosing the quality of those weights. The package includes a vignette containing some basic theory and walks through two examples. It is available by