similar to: partial dependence plots in 'party'

Hi everybody, I used random forest regression to explain the patterns of species richness and a bunch of climate variables (e.g. Temperature, precipitation, etc.) All are continuos variables. My results are really interesting and my model explained 96,7% of the variance. Now I am trying to take advantage of the importance variable function and depicts the observed patterns using partial

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

Hello ALL, I'm unsure how to interpret partial dependence plots and had 2 questions: Does the randomForest library scale partial dependence plots such that zero on the y axis is mean(y)? I am also unclear as to why the range of y on these plots is smaller than what is in the dataset. Also I have noticed that partial dependence plots cluster around the mean response. That is, if I'm

Hi, I'm trying to make a partial plot with package randomForest in R. After I perform my random forest object I type partialPlot(data.rforest, pred.data=act2, x.var=centroid, "C") where data.rforest is my randomforest object, act2 is the original dataset, centroid is one of the predictor and C is one of the classes in my response variable. Whatever predictor or response class I

Help, I've been having a difficult time trying to create 3d partial dependence plots using "rgl". It looks like this question has been asked a couple times, but I'm unable to find a clear answer googling. I've tried creating x, y, and z variables by extracting them from the partialPlot output to no avail. I've seen these plots used several times in articles, and I

Dear List, I would greatly appreciate help on the following matter: The RuleFit program of Professor Friedman uses partial dependence plots to explore the effect of an explanatory variable on the response variable, after accounting for the average effects of the other variables. The plot method [plot(summary(rq(y ~ x1 + x2, t=seq(.1,.9,.05))))] of Professor Koenker's quantreg program

Hello all~ I am interested in clarifying something more conceptual, so I won't be providing any data or code here. >From what I understand, partial dependence plots can help you understand the relative dependence on a variable, and the subsequent values of that variable, after "averaging out the effects" of the other input variables. This is great, but what I am interested in

Hello, I am running randomForest models on a number of species. I would like to be able to automate the printing of dependence plots for the most important variables in each model, but I am unable to figure out how to enter the variable names into my code. I had originally thought to extract them from the $importance matrix after sorting by metric (e.g. %IncMSE), but the importance matrix is n

> > I would like to build a forest of regression trees to see how well some > covariates predict a response variable and to examine the importance of > the > covariates. I have a small number of covariates (8) and large number of > records (27368). The response and all of the covariates are continuous > variables. > > A cursory examination of the covariates does not

Hello, I'm facing a strange behaviour when I try to run predict function for a cforest model from party package in CentOS. It works OK on MacOSX and Ubuntu, but R process is killed when I try it on CentOS. I read a dataframe and generate a forest model using cforest from party package. To reduce computation for the tests I'm running the forest model with 2 (two) trees only. So I believe

I'm pretty new to R, and not much of a progammer (yet). I'm having trouble navigating the graphical output for the party algorithm. Essentially, my tree is too large for the default page size so the nodes overlap and obscure one another. Anybody know how to change the plot parameters to either: 1) enlarge the page size so the default font fits comfortably (preferred); 2)

Dear useRs, Version 0.8-1 of the `party' package will appear on CRAN and its mirrors in due course. This version implements two new tools: o `mob', an object-oriented implementation of a recently suggested algorithm for model-based recursive partitioning (Zeileis, Hothorn, Hornik, 2005) has been added. It works out of the box for partitioning (generalized) linear

I would like to build a forest of regression trees to see how well some covariates predict a response variable and to examine the importance of the covariates. I have a small number of covariates (8) and large number of records (27368). The response and all of the covariates are continuous variables. A cursory examination of the covariates does not suggest they are correlated in a simple fashion

Dear mailing list, I am using the cforest() method from the party package to train a randomForest with ten input parameters which sometimes contain "NA"s. The predicted variable is a binary decision. Building the tree works fine without warnings or error messages, but when using the predict() statement for validation, I run in an error: forest <- cforest(V31 ~ V1+V2+V3,

When plotting Binary Trees (ctree) from the party package, is there a way to adjust the font sizes of the leaves? require(party) irisct <- ctree(Species ~ ., data = iris) plot(irisct) I want to adjust the font sizes for "Node 2", "Node 5", etc. I'd also like to be able to adjust the font sizes for the x-axis and y-axis labels of the histograms. Thanks,

Hello, I need to draw a partial dependence bar graph. My the my predictor vectors are continous and so is the response variable. Iam using the partialPlot function of the randomForest package. I get a line graph. How can I edit it to get a bar graph instead? (partialPlot(randomForest object ,data-matrix, number of predictor vectors, "Temp")) -- Daudi Jjingo [[alternative HTML

Dear R-developers, since R 2.15.2 I?m getting an error with my RNetLogo package. The package uses rJava and connects to the Java program NetLogo (http://ccl.northwestern.edu/netlogo/). When starting it in so-called GUI-mode, i.e.: library(RNetLogo) NLStart("C:/Program Files/NetLogo 5.0.3", gui=T) #replace the path with the path to your NetLogo installation directory on a 32-bit

Hi all, The 2 day meetBSD conference and FreeBSD 15 year Anniversary party at the Googleplex in Mountain View, California on November 15th and 16th is a little over 3 weeks away! If you haven't registered for the conference yet, please do so if you are planning on attending. The conference is free to attend and the party is $50 dollars for you and a guest. This includes catered dinner and

Dear users, I have two continuous variables which are two different measures taken each year from 1975 to 2005. I want to see if the two variables are correlated but need to take into account the fact that they are a time series. I have been following an example from 'The R Book' where you plot the ACF: par(mfrow=c(1,1) acf(cbind(x,y)) and this appeared to work fine, producing four

Dear all, I would like to draw three forest plots to represent results at years 1, 2 and 3. I have the data as point estimates and 95% confidence intervals. Using the following code I can get three basic forest plots - the first which has the table of results. I have to plot each separately as the usual par(mfrow=c(3,1)) does not work with the function forestplot within rmeta. I can easily put