similar to: SAMBA in separate Domains/Forests ...

Well I'm hoping someone here can give me some assistance. Where I work we manage multiple AD forests. We are looking for a way to centrally manage this. Right now each forest has its own logins for our support people here. I hoping there's a way to make samba make this a bit easier. I know samba will do domain trusts, but is there a way to have it have do trusts to each seperate forest.

So I've been working with Random Forests ( R library is randomForest) and I curious if Random Forests could be applied to classifying on a real time basis. For instance lets say I've scored fraud from a group of transactions. If I want to score any new incoming transactions for fraud could Random Forests be used in that context. Linear Regression is nice in that it is very easy to

Dear all, I would like to use a tree regression method to analyze my dataset. I am interested in the fact that random forests creates in-bag and out-of-bag datasets, but I also need an estimate of support for each split. That seems hard to do in random forests since each tree is grown using a subset of the predictor variables. I was thinking of setting mtry = number of predictor variables,

Hi, I have the following situation: I'm designing a solution for an organization with two Active Directory forests. The forests do not have a trust relationship, and there is no chance to get them to move to a trust relationship (at least within a reasonable timescale). I need to set up a fileserver than both sets of users can access, with Windows authentication. I could host this on a UNIX

We implement a Multiple-Forests - Super Admin Domain Model based on : https://technet.microsoft.com/en-us/library/cc546821.aspx We have 2 forests using W2K12r2 : RSC for resources and ADM for admin user accounts. We join linux server to RSC with ADM credential : # net ads join -U linuxadm at ADM.LAB We have a problem when we had to read uidNumber and gidNumber from ADM Forest. Winbind try to

I am trying to use the random forests package for classification in R. The Variable Importance Measures listed are: -mean raw importance score of variable x for class 0 -mean raw importance score of variable x for class 1 -MeanDecreaseAccuracy -MeanDecreaseGini Now I know what these "mean" as in I know their definitions. What I want to know is how to use them. What I am trying to

Hi all, I have a strange problem when applying RF in R. I have a set of variables with which I obtain an AUC of 0.67. I do have a second set of variables that have an AUC of 0.57. When I merge the first and second set of variables, the AUC becomes 0.64. I would expect the prediction to become better as I add variables that do have some predictive power? This is even more strange as the AUC

Hello, I'm trying to sample in Random Forests by a factor, but it is a regression problem and I can't figure out how to do this (I can only see how to sample by strata in classification). Thanks Jesse Lasky

Hello, I was wondering if anyone knew of an R function/R code to plot bivariate (3 dimensional) partial dependence plots in random forests (randomForest package). It is apparently possible using the rgl package (http://esapubs.org/archive/ecol/E088/173/appendix-C.htm) or there may be a more direct function such as the pairplot() in MART (multiple additive regression trees)? Many

I understand the original implementation of Random Forest was done in Fortran code. In the source files of the R implementation there is a note "C wrapper for random forests: get input from R and drive the Fortran routines.". I'm far from an expert on this...does that mean that the implementation in R is through calls to C functions only (not Fortran)? So, would knowing C be

Hello! I think I am relatively clear on how predictor importance (the first one) is calculated by Random Forests for a Classification tree: Importance of predictor P1 when the response variable is categorical: 1. For out-of-bag (oob) cases, randomly permute their values on predictor P1 and then put them down the tree 2. For a given tree, subtract the number of votes for the correct class in the

Dear Random Forests gurus, I have a question about R^2 provided by randomForest (for regression). I don't succeed in finding this information. In the help file for randomForest under "Value" it says: rsq: (regression only) - "pseudo R-squared'': 1 - mse / Var(y). Could someone please explain in somewhat more detail how exactly R^2 is calculated? Is "mse"

Full_Name: Daniel Normolle Version: 2.0.1 OS: Linux/Fedora Core 3 Submission from: (NULL) (141.214.17.5) varImpPlot in Random Forests 4.5-10 produces the error "incorrect number of subscripts on matrix" (and no plot) when applied to a randomForest object. This error did not occur with 4.5-4 or earlier versions.

I am hoping someone can shed some light on this. We have a setup that is using Active Directory Windows 2008 R2 with 2 domains, A and B. They are across forests, with a one-way trust between the forests. A is the trusted domain, B is the trusting domain. We have a 3.6.9 samba server joined to B's Active Directory. If we try authenticating from our machine in B's domain as a user from A

Hi all, With the new company wide AD setup, there are two forest, the first is the production AD forest and the second is the development/engineering AD forest. For a variety of reasons we need to have a samba server in both AD forests that access data on the same solaris file server. I saw the sections in the samba official howto have multiple virtual server on the same host. However what I

Hi there We have a bunch of Win2K3 trusted domains that are parts of other forests from our own Win2K3 forest. Most times Samba works just fine with allowing users from such trusted domains to connect to its shares, but now and then it "gets out of whack" and loses access/information about these "other" domains. "log level = 9" shows things like the following where

Hi, I am currently writing code to input a few thousand files, run them through the Random Forests package, and then output corresponding results. When I use the code below: zz<-textConnection("ex.lm.out", "w") sink(zz)

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

On Thu, Dec 08, 2016 at 12:19:08PM +0100, Karim Ayari via samba wrote: > We implement a Multiple-Forests - Super Admin Domain Model based on : > > https://technet.microsoft.com/en-us/library/cc546821.aspx > > We have 2 forests using W2K12r2 : RSC for resources and ADM for admin user > accounts. > > We join linux server to RSC with ADM credential : > > # net ads