Displaying 20 results from an estimated 10000 matches similar to: "Rpart and case weights: working with functions"
2008 Oct 23
3
xy.coords in text
Hello,
I want to add text annotation about correlation on "pairs" plots. I
found that I could pass a function to the "panel" argument of pairs :
panel.annot <- function(x, y, ...) {
points(x, y, ...)
c <- cor.test(x, y)
legend("topleft", legend=substitute(rho == r, list(r=sprintf("%.2f",
c$estimate))), bty="n")
}
And then :
2008 Oct 29
0
Propagate vector attributes to data frame
Hello,
I've got a function that takes a numeric vector (x), computes a
transformation value (myAttr) for x, transforms x according to myAttr
and then sets myAttr as an attribute of x before returning x, so I can
easily know what myAttr was used (basically it's a power transformation
and myAttr is the lambda).
myFunction.numeric <- function(x, ...) {
myAttr <- calcMyAttr(x, ...)
x
2008 Mar 06
1
Rpart and bagging - how is it done?
Hi there.
I was wondering if somebody knows how to perform a bagging procedure on a
classification tree without running the classifier with weights.
Let me first explain why I need this and then give some details of what I
have found out so far.
I am thinking about implementing the bagging procedure in Matlab. Matlab
has a simple classification tree function (in their Statistics toolbox) but
2005 Oct 08
1
Rpart -- using predict() when missing data is present?
I am doing
> library(rpart)
> m <- rpart("y ~ x", D[insample,])
> D[outsample,]
y x
8 0.78391922 0.579025591
9 0.06629211 NA
10 NA 0.001593063
> p <- predict(m, newdata=D[9,])
Error in model.frame(formula, rownames, variables, varnames, extras, extranames, :
invalid result from na.action
How do I persuade him to give me NA
2006 Sep 10
1
Rpart, custom penalty for an error
Hello all R-help list subscribers,
I'd like to create a regression tree of a data set with binary response
variable. Only 5% of observations are a success, so the regression tree
will not find really any variable value combinations that will yield
more than 50% of probability of success. I am however interested in
areas where the probability of success is noticeably higher than 5%, for
2007 Jul 08
1
rpart weight prior
Hi!
Could you please explain the difference between "prior" and "weight" in
rpart? It seems to be the same. But in this case why including a weight
option in the latest versions? For an unbalanced sampling what is the
best to use : weight, prior or the both together?
Thanks a lot.
Aur?lie Davranche.
2011 Dec 27
0
Using minsplit and unequal weights in rpart
Dear r-help mailing list,
Is there a way to incorporate weights into the minsplit criteria in rpart,
when the weights are uneven? I could not find a way for the minsplit
threshold to take the weights into account, and when the weights are uneven
it becomes an issue, as the following example shows.
My current workaround is to expand the data into one in which each row is
an observation, but that
2007 Feb 18
3
User defined split function in rpart
Dear R community,
I am trying to write my own user defined split function for rpart. I read
the example in the tests directory and I understand the general idea of the
how to implement user defined splitting functions. However, I am having
troubles with addressing the data frame used in calling rpart in my split
functions.
For example, in the evaluation function that is called once per node,
2009 May 08
1
Get (feature, threshold) from Output of rpart() for Stump Tree
Hi,
I have a question regarding how to get some partial information
from the output of rpart, which could be used as the first argument to
predict. For example, in my code, I try to learn a stump tree (decision
tree of depth 2):
"fit <- rpart(y~bx, weights = w/mean(w), control = cntrl)
print(fit)
btest[1,] <- predict(fit, newdata = data.frame(bx)) "
I found
2004 May 07
0
rpart for CART with weights/priors
Hi,
I have a technical question about rpart:
according to Breiman et al. 1984, different costs for misclassification in
CART can be modelled
either by means of modifying the loss matrix or by means of using different
prior probabilities for the classes,
which again should have the same effect as using different weights for the
response classes.
What I tried was this:
library(rpart)
2006 Jul 21
2
rpart unbalanced data
Hello all,
I am currently working with rpart to classify vegetation types by spectral
characteristics, and am comming up with poor classifications based on the fact
that I have some vegetation types that have only 15 observations, while others
have over 100. I have attempted to supply prior weights to the dataset, though
this does not improve the classification greatly. Could anyone supply some
2007 Jan 25
1
rpart question
I make classification tree like this code
p.t2.90 <- rpart(y~aa_three+bas+bcu+aa_ss,
data=training,method="class",control=rpart.control(cp=0.0001))
Here I want to set weight for 4 predictors(aa_three,bas,bcu,aa_ss).
I know that there is a weight set-up in rpart.
Can this set-up satisfy my need?
If so, could someone give me an example?
Thanks,
Aimin Yan
2006 Sep 19
3
Problem with rpart
Not sure if anyone has posted on this problem ... I want to use rpart to
build a binary tree on a relatively large dataset with ~1400 data points
and 15 predictors. But I've noticed that rpart fails almost immediately
in the call to C_s_to_rp, as that code returns nonsense. Looking at the
code itself isn't terribly helpful, and there don't seem to be any hard
limits coded anywhere.
2007 Jan 03
1
User defined split function in Rpart
Dear all,
I'm trying to manage with user defined split function in rpart
(file rpart\tests\usersplits.R in
http://cran.r-project.org/src/contrib/rpart_3.1-34.tar.gz - see bottom of
the email).
Suppose to have the following data.frame (note that x's values are already
sorted)
> D
y x
1 7 0.428
2 3 0.876
3 1 1.467
4 6 1.492
5 3 1.703
6 4 2.406
7 8 2.628
8 6 2.879
9 5 3.025
10 3 3.494
2007 Jun 15
2
model.frame: how does one use it?
Philipp Benner reported a Debian bug report against r-cran-rpart aka rpart.
In short, the issue has to do with how rpart evaluates a formula and
supporting arguments, in particular 'weights'.
A simple contrived example is
-----------------------------------------------------------------------------
library(rpart)
## using data from help(rpart), set up simple example
myformula <-
2008 Jul 22
2
rpart$where and predict.rpart
Hello there. I have fitted a rpart model.
> rpartModel <- rpart(y~., data=data.frame(y=y,x=x),method="class", ....)
and can use rpart$where to find out the terminal nodes that each
observations belongs.
Now, I have a set of new data and used predict.rpart which seems to give
only the predicted value with no information similar to rpart$where.
May I know how
2009 Jun 09
3
rpart - the xval argument in rpart.control and in xpred.rpart
Dear R users,
I'm working with the rpart package and want to evaluate the performance of
user defined split functions.
I have some problems in understanding the meaning of the xval argument in
the two functions rpart.control and xpred.rpart. In the former it is defined
as the number of cross-validations while in the latter it is defined as the
number of cross-validation groups. If I am
2005 Aug 26
1
Help in Compliling user -defined functions in Rpart
I have been trying to write my own user defined function in Rpart.I
imitated the anova splitting rule which is given as an example.In the
work I am doing ,I am calculating the concentration index(ci) ,which
is in between -1 and +1.So my deviance is given by
abs(ci)*(1-abs(ci)).Now when I run rpart incorporating this user
defined function i get the following error message:
Error in
2018 Aug 14
2
Xenial rpart package on CRAN built with wrong R version?
Hello,
I just upgraded my Ubuntu Xenial system to R 3.5.1 (from 3.4.?) by changing the sources.list entry and doing an "apt-get dist-upgrade". Everything works except loading the rpart package in R:
> library(rpart)
Error: package or namespace load failed for ?rpart?:
package ?rpart? was installed by an R version with different internals; it needs to be reinstalled for use with
2004 May 13
2
R 1.9.0 and pred.rpart
I have just upgraded from R 1.7.3 to R 1.9.0 and have found that the
predict function no longer works for rpart:
> predict(hmmm,sim3[1:10,])
Error in predict.rpart(hmmm, sim3[1:10, ]) :
couldn't find function "pred.rpart"
I have re-installed the rpart package to no avail. Any ideas?
Giles Hooker