On 06/01/11 23:10:59, Noah Silverman wrote:
> I have a data set with about 30,000 training cases and 103 variable.
> I've trained an SVM (using the e1071 package) for a binary classifier
> {0,1}. The accuracy isn't great. I used a grid search over the C and G
> parameters with an RBF kernel to fi
On 16/12/10 15:12:47, Holger Hoefling wrote:
> Specifically I want all objects in the workspace removed
rm(list=ls()) should do this trick.
> and all non-base packages detached and unloaded
You may obtain the list of loaded packages via
(.packages())
Store this at the beginning of your session
On 10/12/10 23:26:28, dorina.lazar wrote:
> I am looking for a clustering method usefull to classify the countries in
> some clusters taking account of: a) the geographical distance (in km)
> between countries and b) of some macroeconomic indicators (gdp, life
> expectancy...).
Hi Dorina,
before
On 10/12/10 03:45:46, sadanandan wrote:
> I am trying to develop a neural network with single target variable and 5
> input variables to predict the importance of input variables using R. I used
> the packages nnet and RSNNS. But unfortunately I could not interpret the out
> put properly and the do
On 10/12/10 02:56:13, jothy wrote:
> Am working on neural network.
> Below is the coding and the output [...]
> > summary (uplift.nn)
>
> a 3-3-1 network with 16 weights
>
> options were -
>
> b->h1 i1->h1 i2->h1 i3->h1
> 16.646.62 149.932.24
> b->h2 i1->h2 i2->h2 i3->h2
> -4
Hi there,
this is more a comment and a solution rather than a question, but I
thought I'd post it since it cost some time to dig down to the issue and
maybe someone else could run into this.
I'm using the nnet function for a regression task. I'm inputting the
following data frame:
> 'data.frame'
On 03/12/10 16:23:33, manuel.martin wrote:
> I am currently looking for a book about support vector machines for
> regression and classification and am a bit lost since they are plenty of
> books dealing with this subject. I am not totally new to the field and
> would like to get more information o
On 02/12/10 17:49:37, Andrew Agrimson wrote:
> I've been comparing results from kmeans() in R to PROC FASTCLUS in SAS
> and I'm getting drastically different results with a real life data set.
> [...] Has anybody looked into the differences in the implementations or
> have any thoughts on the matte
On 30/11/10 10:10:07, Baoqiang Cao wrote:
> I'd like to download some data files from a remote server, the problem
> here is that some of the files actually don't exist, which I don't
> know before try. Just wondering if a function in R could tell me if a
> file exists on a remote server?
Hi Baoq
On 29/11/10 11:57:31, Jude Ryan wrote:
>Hi Georg,
>
>
>The documentation (?nnet) says that y should be a matrix or data frame,
>but in your case it is a vector. This is most likely the problem, if
>you do not have other data issues going on. Convert y to a matrix (or
>data frame
On 27/11/10 19:04:27, Serdar Akin wrote:
>Hi
>No its has to be like this:
>a b
>1 1
>2 2
>3 3
> 4
> 5
> 6
Hmm, "empty" elements in such an array? Seems not really recommended, if
it's possible at all. You may try filling up the shorter vector with NA's
or any
On 27/11/10 16:04:35, Serdar Akin wrote:
> I'm trying two combine two vectors that have different lengths. This without
> recursive the shorter one. E.g.,
>
> a <- seq(1:3)
> b <- seq(1:6)
If that means your output should be (1 2 3 1 2 3 4 5 6) then
c <- c(a,b) should solve this. Looks like _the_
Hi,
I'm currently trying desperately to get the nnet function for training a
neural network (with one hidden layer) to perform a regression task.
So I run it like the following:
trainednet <- nnet(x=traindata, y=trainresponse, size = 30, linout = TRUE,
maxit=1000)
(where x is a matrix and y a n
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