Bryan:
Hi,
I was wondering if Statdataml is currently the preferred way to
represent statistical data in XML in R.
This is hard to tell. We think it is a _possible_ way doing that. Do you
have some alternatives in mind?
And also if the Statdataml api
provides ways to load the XML as a
Hi all,
there is tune() in the e1071 package for doing this in general, and,
among others, a tune.nnet() wrapper (see ?tune):
tmodel = tune.nnet(Species ~ ., data = iris, size = 1:5)
summary(tmodel)
Parameter tuning of `nnet':
- sampling method: 10-fold cross validation
- best
., symmetry,
transitivity, etc.).
David and Kurt.
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Dr. David Meyer
Department of Information Systems and Operations
Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Tel: +43-1-313 36 4393
Fax: +43-1-313 36 90 4393
HP: http://wi.wu
Dear useRs,
a new package for computing distance and similarity matrices made it to
CRAN, and will propagate to the mirrors soon.
It includes an enhanced version of dist() with support for more than
40 popular similarity and distance measures, both for auto- and
cross-distances. Some
Chris:
yes, this is indeed a bug (in predict.svm) - will be fixed in the next
release of e1071.
Thanks for pointing this out,
David
--
Hello all,
I am trying to use the svm method provided by e1071 (Version: 1.5-16)
together with a matrix provided by the SparseM
Adschai:
The function is written in C++, so debugging the source code of the R
svm() function will not really help. What you can do to make the C-code
more verbose is the following:
- get the sources of e1071
- in the src/ directory, look up the svm.cpp file
- In line 37, there is:
#if 0
Adschai:
here is an example for class.weights (isn't it on the help page?):
data(iris)
i2 - iris
levels(i2$Species)[3] - versicolor
summary(i2$Species)
wts - 100 / table(i2$Species)
wts
m - svm(Species ~ ., data = i2, class.weights = wts)
Cheers,
David
Dear useRs,
it is our great pleasure to announce the new package relations to
appear on all CRAN-mirrors soon.
This package provides data structures and methods for creating and
manipulating relations, relation ensembles, sets, and tuples. The
feature list includes:
* creation of relations by
It's in package cba (sdists()).
David
--
I have a column of words, for example
DOG
DOOG
GOD
GOOD
DOOR
...
and I am interested in creating a matrix that contains the string
edit distances between each pair of words. I am this close - ' '
- to writing the algorithm myself
Oldrich:
The columns in data passed to svm need to contain only numeral values.
This is not correct, svm() of course also accepts factors and then
builds a model matrix similar to lm(). But it won't accept, e.g.,
character vectors.
I simply assigned a number to each category of each
Hello:
Does anyone know if there exists a package that handles methods for [
for
dist objects?
I would like to access a dist object using matrix notation
e.g.
dMat = dist(x)
dMat[i,j]
You can use the [[ operator defined for distance matrices currently
!
--
Dr. David Meyer
Department of Information Systems and Operations
Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Tel: +43-1-313 36 4393
Fax: +43-1-313 36 90 4393
HP: http://wi.wu-wien.ac.at/~meyer
Hello (whoever you are),
your data looks problematic. What does
head(ne_span_data)
reveal?
BTW, svm() will not handle NA values.
Best
David
-
Hello. I'm new to R and I'm trying to solve a classification problem. I have
a training dataset of about 40,000 rows and 50
David:
I ‘m trying to draw ONE table that summarize SEVERAL categorical
variables
according to one classification variable, say “sex”. The result would
look
like several contingency tables appended one to the other. All the
variables
belong to a data frame.
The summary.formula in
Aimin:
The problem is that the columns you choose for training (only 4
variables) do not match the ones used for prediction (all except y).
David
I try to use naiveBayes
p.nb.90-naiveBayes(y~aa_three+bas+bcu+aa_ss,data=training)
. it doesn't work.
It is pity not saving my original code.
Now the question is the plot I get using your code is different from
what I got before.
Moreover I did remember I use plot(m.svm,p5.new,As~Cur)
Do you know why?
Thanks,
Aimin
At 06:32 AM 12/8/2006, David Meyer wrote:
Aimin:
1
.new,As~Cur)
Error in scale(newdata[, object$scaled, drop = FALSE], center =
object$x.scale$scaled:center, :
(subscript) logical subscript too long
--
Dr. David Meyer
Department of Information Systems and Operations
Vienna University of Economics and Business Administration
version of R is this? R-2.4.0, R-patched or
R-devel?
--
Dr. David Meyer
Department of Information Systems and Operations
Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Tel: +43-1-313 36 4393
Fax: +43-1-313 36 90 4393
HP: http://wi.wu
Vince:
the implementations for both are different, so this might happen
(although undesirably).
Can you provide me an example with data (off-list)?
David
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PLEASE do
by
testing whether the 2 odds ratios are the same?
--
Dr. David Meyer
Department of Information Systems and Operations
Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Tel: +43-1-313 36 4393
Fax: +43-1-313 36 90 4393
HP: http://wi.wu-wien.ac.at
the package e1071) but
I have not succeed.
Does anyone knows a way to get that value?
Pau
--
Dr. David Meyer
Department of Information Systems and Operations
Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Tel: +43-1-313 36 4393
Fax: +43-1-313 36
-.default(`*tmp*`, value = c(1, 2, 3, 4, 5, :
'names' attribute [175] must be the same length as the vector [50]
What am I missing? Why would the row names have to be the same?
Thanks so much,
Sandra McBride
--
Dr. David Meyer
Department of Information Systems and Operations
Vienna
Dieter,
there is no way of fixing the range of the residuals yet, we will add sth.
like a ylim argument to legend_foo().
Thanks for pointing this out,
David
PS: there is no mosaicplot() function in vcd, but a mosaic() ...
--
Dr. David Meyer
Department of Information Systems and Operations
~., data = cats)
plot(m, cats)
I don't see what the difference between their example and mine.
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Dr. David Meyer
Department of Information Systems and Operations
Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Fax: +43-1-313 36x746
Tel
:
How can one (elegantly) calculate the distance between data points (in the
transformed space, I suppose) and the hyperplane that separates the 2
categories when using svm() from the e1071 library?
thanks a lot,
Hans
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Department of Information Systems and Operations
Vienna
]
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PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html
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Dr. David Meyer
Department of Information Systems and Operations
Vienna University of Economics and Business
pairs_diagonal_text() for pairs()
* The alternative legend function legend_fixed() now looks more similar
to the legend of mosaicplot() in base R
Comments are more then welcome!
David, Achim, Kurt.
PS: If you like modern art, try out demo(mondrian)! :)
--
Dr. David Meyer
Department of Information Systems
Well, since knn() can't handle incomplete data as it says, you can
choose to either omit incomplete observations (e.g., using na.omit()),
or to impute the data if the conditions are met (missingness at random,
...); see, e.g., packages cat, mix, norm, and e1071 for that.
HTH,
David
http://mail.yahoo.com
--
Dr. David Meyer
Department of Information Systems and Operations
Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Fax: +43-1-313 36x746
Tel: +43-1-313 36x4393
HP: http://wi.wu-wien.ac.at/~meyer
.
Cheers,
David
Its possible that what works already is enough for Amir. For example,
library(e1071)
library(dyn)
set.seed(1)
y - ts(rnorm(100))
y.svm - dyn$svm(y ~ lag(y))
yp - predict(y.svm)
ts.plot(y, yp, col = 1:2)
On 8/12/05, David Meyer [EMAIL PROTECTED] wrote:
Amir
for class one, 49 for class 2. How do I
do that? Just weights=49?
Meanwhile I'd like to try svm(e1071), again, how do I setup
class.weights? Thanks.
--
Dr. David Meyer
Department of Information Systems and Operations
Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien
. David Meyer
Department of Information Systems and Operations
Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Fax: +43-1-313 36x746
Tel: +43-1-313 36x4393
HP: http://wi.wu-wien.ac.at/~meyer/
___
R
completely wrong ... or obvious. Will the svm automatically expand the
factors into a binary matrix?
yes.
If I add numeric variables outside the range of 0 to 1 do I have to
scale them to have 0 to 1 range?
svm() will scale your data by default.
Cheers,
David
--
Dr. David Meyer
Dear David, Dear Friends,
After any running svm I receive different results of Error estimation
of 'svm' using 10-fold cross validation.
using tune.svm(), or the `cross' parameter of svm()?
What is the reason ? It is caused by the algorithm, libsvm , e1071 or
something els?
The
Vivek,
I certainly would agree that every help page, including the one of
svm(), could be improved, but I think it is not _that_ deficient. In
particular, it tells you which parameters are used in the various
kernels available.
Have you read the corresponding article in R News (basically
Stephen:
you need to supply the parameter ranges, your call did not tune anything
at all.
best.svm() is really just a wrapper for tune.svm(...)$best.model. The
help page for 'tune()' will tell you more on the available options.
HTH,
David
[...]
svm.model =
( ) ?
these are not possible? I receive only Error estimation of 'svm'
with model and summary(model) functions.
Clear from the above, I think.
HTH,
David
Best Wishes and so many thanks,
Amir
--
Dr. David Meyer
Department of Information Systems and Process Management
Vienna University
Thank you for your answer,
but my problem concerns the support vectors. Indeed the two classes
are well separated and the hyperplane is linear but the support
vectors aren't aligned in parallel to the hyperplane. And according to
me, the support vectors (for each class) should be aligned
--
Dr. David Meyer
Department of Information Systems and Process Management
Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Fax: +43-1-313 36x746
Tel: +43-1-313 36x4393
HP: http://wi.wu-wien.ac.at/~meyer
ALERT!
This e-mail, in its original form, contained one or more attached files that
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Joao:
1) The error message you get when setting nu=0 is due to the fact that
no support vectors can be found with that extreme restriction, and this
confuses the predict function (try svm(, fitted = false): the model
returned is empty). In fact, the C++ code interfaced by svm() clearly
allows
This is a bug, thanks for pointing this out.
Fixed for the next release of e1071.
David
-
Hello,
I would like to read and write sparse matrices using the
functions write.matrix.csr() and read.matrix.csr()
of the package e1071. Writing is OK but reading back the
matrix fails:
Raj:
The references given on the help page will tell you.
Best,
David
-
Hi All,
In package e1071 for SVM based classification, one can get a probability
measure for each prediction. I like to know what is method that is used
for
calculating this probability. Is it calculated using
I updated the e1071 package but still can't find
the other three arguments for plot.svm.
It's in e1071 since version 1.5-3. (current version: 1.5-4).
In addition, I can plot a
gray-colored contour region by adding the argument col = c(gray(0.2),
gray(0.8)). But I failed to change those
0x. Der Vorgang read konnte nicht auf dem Speicher
ausgef_hrt werden. .
Which version of e1071 are you using?
There has been a memory leak problem until 1.5-1 which could very well
cause this null pointer exception...
best,
David
--
Dr. David Meyer
Department of Information Systems
-regression. It is an omission in the ?svm help page? Or am I
notundestanding something?
I believe it has something to do with the calculus of the eigenvalues.
Anyway
how can I overpass this problem? Increasing the training data (is around
900
records)?
Thanks for any help
Joao
--
Dr. David
. David Meyer
Department of Information Systems
Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Fax: +43-1-313 36x746
Tel: +43-1-313 36x4393
HP: http://wi.wu-wien.ac.at/~meyer/
__
[EMAIL PROTECTED
of predicted
values.
Best,
-d
Thank you very much,
Frank
--
Dr. David Meyer
Department of Information Systems
Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Fax: +43-1-313 36x746
Tel: +43-1-313 36x4393
HP: http://wi.wu-wien.ac.at/~meyer
Uwe:
[the language of the list is English!]
Try using a *factor* for classification. The described behavior
(segfault when using class.weights with a *numeric* dependent variable)
should be fixed in the current version of e1071 (1.5-2), so please check
if you are using the latest version of
but it seems a
good way to measure if your results might be by chance.
Two questions:
Any comments on Kappa and what it might be telling me?
What can I do to tune my kernels further?
Stephen
--
Dr. David Meyer
Department of Information Systems
Vienna University of Economics and Business
; charset=ISO-8859-1
Does anyone knows what is the nu-regression option for the type
parameter in svm (from package e1071)? I cannot find any explanation
on that and I have a reasonable understanding on svm fundamentals.
Thanks
Joao Moreira
-
David Meyer
Department of Information
might want to check if
your target variable is indeed a factor. In case it is and you still get
values greater than 1, drop me a mail with a piece of code (and data)
enabling me to reproduce the phenomenon.
Best,
David
--
Dr. David Meyer
Department of Information Systems
Vienna University
Have you considered the read.matrix.csr() function in pkg. e1071? It
uses another sparse input format, but perhaps you can easily transform
your data in the supported one. Also, in my experience, data frames are
not the best basis for a sparse format since they might turn out to be
very memory
validation out the svm? I mean e.g. numbers about the true
positives ,fp,fn,tf ?
No, because the accuracies are not computed using a confusion matrix.
The computation is internally done in C.
How do I get a list of the classified examples ?
--
Dr. David Meyer
Department of Information Systems
You could look at
@Article{ e1071-papers:meyer+leisch+hornik:2003,
author= {David Meyer and Friedrich Leisch and Kurt Hornik},
title = {The Support Vector Machine under Test},
journal = {Neurocomputing},
year = 2003,
month = {September
You might consider using the `weight' argument of svm().
Best,
David.
Hi!
I am using R 1.8.1 and the svm of the e1071 package for classification.
The problem is that I have unbalanced classes e.g. the first one is much
bigger than the second one and therfore the svm is biased to the first
On Mon, 3 Nov 2003 [EMAIL PROTECTED] wrote:
I am trying to understand what is the difference between linear and
polynomial kernel:
linear: u'*v
polynomial: (gamma*u'*v + coef0)^degree
It would seem that polynomial kernel with gamma = 1; coef0 = 0 and degree
= 1
On Fri, 31 Oct 2003 [EMAIL PROTECTED] wrote:
rng - list(gamma = 2^(-1:1), cost = 2^(2:4))
rng
$gamma
[1] 0.5 1.0 2.0
$cost
[1] 4 8 16
obj - tune.svm(pIC50 ~ ., data = data, ranges = rng)
Error in tune(svm, train.x = x, data = data, ranges = ranges, ...) :
formal
This suggests to me that data are scrambled each time - the last time I
looked at libsvm python interface
this is what was done. Is this the same here (I hope) ?
yes.
g.,
David
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If I try the model below, R seems to grumble with a complaint.
glm(cbind(Y,1-Y) ~ X, family = binomial)
non-integer counts in a binomial glm! in: eval(expr, envir, enclos)
For binomial models (as described in the help page), the response must be
either a factor or a n x 2 matrix with
Is there an alternative way of dispatching the printing, such that
the usual print method for loglm is used after doing what is special
for hllm?
You might want to have a look at `NextMethod()'
Best,
David
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will change the code to give a better error message in
such cases.
Best,
David.
On 2003.09.03 18:32, Luis Miguel Almeida da Silva wrote:
The data goes in attachment. I used ts to create data.ts
data.ts-ts(data=data,start=c(2001,1),frequency=12)
-Original Message-
From: David Meyer
And in package vcd function ternaryplot().
g.,
-d
On 2003.07.15 09:33, Tobias Verbeke wrote:
Are there enough geochemists using R already that he'd find
like-minded people to discuss technical issues with if he _did_
switch to R? Is there a package somewhere already that does ternary
and
Andrew,
1) The current R version is 1.7.1
2) Which version of `e1071' are you using?
3) Does the `e1071.so' file exist (in e1071/libs)?
best,
David.
On 2003.06.24 21:43, Andrew Perrin wrote:
After upgrading to 1.7.0 under debian linux, I can't get e1071 working
properly.
The first problem I had
On 2003.06.13 02:11, g wrote:
Hi,
Can someone set me straight as to how to write formulas in R to
indicate:
complete independence [A][B][C]
Freq ~ A + B + C
joint independence [AB][C]
Freq ~ A * B + C
conditional independence [AC][BC]
Freq ~ A * C + B * C
nway interaction
On 2003.06.12 09:15, Uwe Ligges wrote:
Iouri Tipenko wrote:
Dear R-Users,
I'm a master student in Mathematics and Statistics at Carleton
University, Ottawa, Canada.
I'm studying Clustering methods including different related
algorithms. One of them is Support Vector Clustering algorithm.
I was
Support Vector Machines
Description:
`svm' is used to train a support vector machine. It can be used
to
carry out general regression and classification (of nu and
epsilon-type), as well as density-estimation. A formula interface
is provided.
David Meyer [EMAIL PROTECTED] wrote
I am trying to compile the package e1071 (version 1.3-11) with R CMD
INSTALL. I tried with R 1.7.0 on Redhat Linux 2.4.7-10 and R 1.6.2 on
Linux 2.4.9-34smp but keep getting the same error message during
configure :
WARNING: g++ 2.96 cannot reliably be used with this package. Please use
Try `goodfit' in package `vcd'.
g.,
-d
Mag. David MeyerWiedner Hauptstrasse 8-10
Vienna University of Technology A-1040 Vienna/AUSTRIA
Department of Tel.: (+431) 58801/10772
Statistics and Probability Theory Fax.: (+431) 58801/10798
On Sat
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