search for: mindev

Dear All, We came across a problem when using the "tree" package to analyze our data set. First, in the "tree" function, if we use the default value "mindev=0.01", the resulting regression tree has a single node. So, we set "mindev=0", and obtain a tree with 931 terminal nodes. However, when we further use the "cv.tree" function to run a 10-fold cross-validation, the error message is: "Error in prune.tree(list(frame = li...

...tree dataset: 100,000 records about 3 variables regression tree data read in from flat file, summary() on R and Splus showed identical distributions tree were run with all the deault setting (no mincut, minsize set etc) with added options: minsize=2, mindev=-1, get the same small tree. Did I miss anything? thanks -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the &quo...

...dows 10 y hoy me tiene loco el siguiente error cuando ejecuto predict para un árbol de clasificación-regresión. El problema da incluso con el ejemplo del comando predict library(tree) data(shuttle, package="MASS") shuttle.tr <- tree(use ~ ., shuttle, subset=1:253, mindev=1e-6, minsize=2) shuttle.tr shuttle1 <- shuttle[254:256, ]  # 3 missing cases predict(shuttle.tr, shuttle1) Da el error: Error in pred1.tree(object, tree.matrix(newdata)) : object 'VR_pred1' not found Sabe alguien ¿cuál es el problema? ¿Os ocurre a vosotros lo mismo? Un cordial saludo...

Hi. I'm trying to get a tree, that fits all the lines of the training set ( a tree with no error in classification) data(iris) tree.control(150,mindev=3D-1,minsize=3D2) ir.tr <- tree(Species ~., iris) ir.tr summary(ir.tr) I'm trying to use this as a test, but it still have some examples that are classified wrongly... Anyone could tell me what's the problem? Thanks -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-...

Hi. I'm using the tree package to fit one tree from a training set. I'm using the command: hm.tr <-tree(X1~.,teste2, mindev = 0, minsize = 2) and i get the error: Error in "row.names<-.data.frame"(*tmp*, value = fit$node[1:n]) : duplicate row.names are not allowed the frameset, has 180 columns and 16000 rows. The first column, takes a value from 42..61 and the oth...

Hi, all, I am wondering if it is possible to set parameters of 'rpart' and 'tree' such that they will produce the exact same tree? Thanks. Auston Wei Statistical Analyst Department of Biostatistics and Applied Mathematics The University of Texas MD Anderson Cancer Center Tel: 713-563-4281 Email: wwei@mdanderson.org [[alternative HTML version deleted]]

...de clasificación-regresión. El > problema da > incluso con el ejemplo del comando predict > > library(tree) > data(shuttle, package="MASS") > shuttle.tr <http://shuttle.tr> <- tree(use ~ ., shuttle, subset=1:253, >                     mindev=1e-6, minsize=2) > shuttle.tr <http://shuttle.tr> > shuttle1 <- shuttle[254:256, ]  # 3 missing cases > predict(shuttle.tr <http://shuttle.tr>, shuttle1) > > Da el error: > > Error in pred1.tree(object, tree.matrix(newdata)) : object 'VR_p...

Hi, I have a dataframe, y, with 1000 rows and 266 columns. The first column of y is a 2 level factor response; columns 2:266 are each ordinal variables that can take on one of the values 1, 2, or 3. I'm trying to fit a model with the calls: (A) y.tree <- tree(pref~.,data=y,mindev=0,minsize=2) and (B) y.tree <- tree(pref~.,data=y,split='gini') pref is the name of the factor response variable. In (A) I can fit a model using only about 600 rows of y before getting the error message below and in (B) I can only use about 100 rows of y before I get the error messag...

Full_Name: Petr Savicky Version: 1.5.0 OS: SuSE 7.2 Submission from: (NULL) (147.231.6.1) The function tree() from the tree package crashes for certain input data. All the information needed to reproduce the error (data, script, expected error message) may be found at http://www.cs.cas.cz/~savicky/tree_error/tree_error.tgz Exactly the same error appeared at another computer running some RedHat

I am using tree() in the library tree to learn regression trees. Once in a while I am getting the error "Tree is too big". From the same data set, but with randomized subsets I am learning several tree model and in the end of the day I would like to look at some of the properties across trees. My problem: I have for loop containing a call to tree(). However, since tree() returns an

Hi all, I am running R1.5.0 under unix. I recently used the function 'predict.tree' to make predictions with a tree object and a dataframe of numeric items. The predict.tree internally, calls a function 'delete.response'. When I removed this function call from the source code of predict.tree, it ran 10 times faster without any differences in the result obtained. The