[R] "interactions" feature in RF?

Hi all, Is there a possibility of getting the "interactions" feature values for the variables of a dataset by applying the Random Forest algorithm? Thanks, Chrysanthi [[alternative HTML version deleted]] __ R-help@r-project.org mailing list h

Re: [R] how to visualize gini coefficient in each node in RF?

icating me that? thanks a lot, chrysanthi 2009/9/29 Liaw, Andy > No. The forest object is too large as is. I didn't think it's worth > the extra memory to store them. They were never kept even in the > Fortran/C code. > > Andy > > From: Chrysanthi A. >

[R] how to visualize gini coefficient in each node in RF?

Dear all, I am working with randomForest package and I am interested in examining the "Gini importance" measures that are used as a general indicator of feature relevance. Is there a possibility of getting the Gini measure that is being estimated in each tree by the output of the getTree() functio

Re: [R] Problem with Random Forest predict

Dear all, I am working with randomForest package and I am interested in examining the "Gini importance" measures that are used as a general indicator of feature relevance. Is there a possibility of getting the Gini measure that is being estimated in each tree by the output of the getTree() functio

[R] Gini importance measure in RF package

Dear all, I am working with randomForest package and I am interested in examining the "Gini importance" measures that are used as a general indicator of feature relevance. Is there a possibility of getting the Gini measure that is being estimated in each tree by the output of the getTree() functio

[R] Gini importance measure in RF package

Dear all, I am working with randomForest package and I am interested in examining the "Gini importance" measures that are used as a general indicator of feature relevance. Is there a possibility of getting the Gini measure that is being estimated in each tree by the output of the getTree() functio

Re: [R] heatmap.2: question regarding the "raw z-score"

differentially expressed in the two subtypes of the disease that I examine. Many thanks, Chrysanthi. 2009/7/8 James W. MacDonald > Hi Chrysanthi, > > > Chrysanthi A. wrote: > >> Hi, >> >> I am analysing gene expression data using the heatmap.2 function in R

[R] heatmap.2: question regarding the "raw z-score"

Hi, I am analysing gene expression data using the heatmap.2 function in R and I was wondering what is the formula of the "raw z-score" bar which shows the colors for each pixel. According to that post: https://mailman.stat.ethz.ch/pipermail/r-help/2006-September/113598.html, it is the (actual val

Re: [R] help with random forest package

a "manually" like this. > predict.randomForest() does all this for you. > > As to individual tree predictions, predict.randomForest() has an option > "predict.all" that you can use. To get the OOB votes, though, you will also > need to look at the output of random

Re: [R] help with random forest package

ed. That's why you may get odd-ball vote fractions even > when you grow 100 trees and expect the votes to be in seq(0, 1, by=0.01).] > > 100% - 2.34% = 97.66%, not 76.6% (I can only assume you had a typo). > > Cheers, > Andy > > -- >

Re: [R] help with random forest package

> > You can take 1 - OOB error rate as the estimate of prediction accuracy (if > you have not selected variables, e.g., using variable importance, in > building the final RF model). > > Andy > > -- > *From:* Chrysanthi A. [mailto:chrys...@gmail.com]

Re: [R] Re : Running random forest using different training and testing schemes

in,] is the training set and data[test,] is the test set. > > Best, > Pierre > -- > *De :* Chrysanthi A. > *À :* r-h...@r-project..org > *Envoyé le :* Dimanche, 12 Avril 2009, 17h26mn 59s > *Objet :* [R] Running random forest using different training an

Re: [R] Running random forest using different training and testing schemes

The trainControl > function can be used to try different resampling schemes. There is also a > package vignette with details. > > Max > > > > On Apr 12, 2009, at 12:26 PM, "Chrysanthi A." wrote: > > Hi, >> >> I would like to run random Forest cl

[R] Running random forest using different training and testing schemes

Hi, I would like to run random Forest classification algorithm and check the accuracy of the prediction according to different training and testing schemes. For example, extracting 70% of the samples for training and the rest for testing, or using 10-fold cross validation scheme. How can I do that

Re: [R] help with random forest package

t; > -- > *From:* Chrysanthi A. [mailto:chrys...@gmail.com] > *Sent:* Wednesday, April 08, 2009 2:56 PM > *To:* Liaw, Andy > *Cc:* r-help@r-project.org > *Subject:* Re: [R] help with random forest package > > Many thanks for the reply. > >

Re: [R] help with random forest package

he varUsed() and getTree() functions. > > Andy > > From: Chrysanthi A. > > Hello, > > > > I am a phd student in Bioinformatics and I am using the Random Forest > > package in order to classify my data, but I have some questions. > > Is there a function in order

[R] help with random forest package

Hello, I am a phd student in Bioinformatics and I am using the Random Forest package in order to classify my data, but I have some questions. Is there a function in order to visualize the trees, so as to get the rules? Also, could you please provide me with the code of "randomForest" function, as