Displaying 20 results from an estimated 10000 matches similar to: "How do I get the parameters out of e1071's svm?"
2005 Jun 28
2
svm and scaling input
Dear All,
I've a question about scaling the input variables for an analysis with svm (package e1071). Most of my variables are factors with 4 to 6 levels but there are also some numeric variables.
I'm not familiar with the math behind svms, so my assumtions maybe completely wrong ... or obvious. Will the svm automatically expand the factors into a binary matrix? If I add numeric
2010 Sep 11
0
[Q] How to extract cross validation results from e1071's svm model
Dear all,
Is it possible to extract cross-validation results from e1071's svm model?
For example, the following R code shows the result from the 10 fold cross-validation.
model = svm(spam ~ ., data = spam, cross = 10)
summary(model)
But, I could not figure out how to get to the accuracy values from the cross-validation. I looked at the svm method, but did not find any return values.
Any
2012 Aug 19
1
e1071 - tuning is not giving the best within the range
Hi everybody,
I am new in e1071 and with SVMs. I am trying to understand the performance
of SVMs but I face with a situation that I thought as not meaningful.
I added the R code for you to see what I have done.
/set.seed(1234)
data <- data.frame( rbind(matrix(rnorm(1500, mean = 10, sd = 5),ncol = 10),
matrix(rnorm(1500, mean = 5, sd = 5),ncol = 10)))
class <- as.factor(rep(1:2,
2011 Jan 07
2
Stepwise SVM Variable selection
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
find the best settings.
I remember that for least squares, R has a nice stepwise function that
will try combining subsets of variables to find
2015 Dec 10
3
SVM hadoop
Estimados
Un día leí algo en el siguiente hipervínculo, pero nunca lo use.
http://blog.revolutionanalytics.com/2015/06/using-hadoop-with-r-it-depends.html
Javier Rubén Marcuzzi
De: Carlos J. Gil Bellosta
Enviado: miércoles, 9 de diciembre de 2015 14:33
Para: MªLuz Morales
CC: r-help-es
Asunto: Re: [R-es] SVM hadoop
No, no correrán en paralelo si usas los SVM de paquetes como e1071.
No
2015 Dec 10
2
SVM hadoop
Hola,
Puedes poner un RStudio en Amazon, poner "caret" y a correr....
No sé si tendrás suficiente con lo que te pueda ofrecer Amazon para tu
problema... creo que sí... ;-)....
O directamente hacerlo aquí, que toda esta instalación ya la tienen hecha:
http://www.teraproc.com/front-page-posts/r-on-demand/
Gracias,
Carlos.
El 10 de diciembre de 2015, 14:43, MªLuz Morales <mlzmrls
2010 Mar 25
1
Manually calculate SVM
Hi,
I'm learning more about SVMs and kernels in general. I've gotten used
to using the svm function in the e1071 package. It works great.
Now, I want to do/learn some more interesting stuff. (Perhaps my own
kernel and/or scoring system). So I want to better understand
1) how calculation of the kernel happens.
2) how to calculate the predicted value (y_hat) given a list of support
2006 Jan 27
1
Classifying Intertwined Spirals
I'm using an SVM as I've seen a paper that reported extremely good
results. I'm not having such luck. I'm also interested in ideas for
other approaches to the problem that can also be applied to general
problems (no assuming that we're looking for spirals).
Here is my code:
library(mlbench)
library(e1071)
raw <- mlbench.spirals(194, 2)
spiral <-
2010 Oct 25
1
online course: SVM in R with Lutz Hamel at statistics.com
Support vector machines (SVMs) have established themselves as
one of the preeminent machine learning models for classification
and regression over the past decade or so, frequently outperforming
artificial neural networks in task such as text mining and
bioinformatics. Dr. Lutz Hamel, author of "Knowledge Discovery with
Support Vector Machines" from Wiley will present his online course
2007 Dec 27
1
(package e1071) SVM tune for best parameters: why they are different everytime i run?
Hi,
I run the following tuning function for svm. It's very strange that every
time i run this function, the best.parameters give different values.
[A]
>svm.tune <- tune(svm, train.x, train.y,
validation.x=train.x, validation.y=train.y,
ranges = list(gamma = 2^(-1:2),
cost = 2^(-3:2)))
# where train.x and train.y are matrix
2003 Jan 31
1
svm regression in R
Hallo,
I have a question concerning SVM regression in R. I intend to use SVMs for feature selection (and knowledge discovery). For this purpose I will need to extract the weights that are associated with my features. I understand from a previous thread on SVM classification, that predictive models can be derived from SVs, coefficiants and rhos, but it is unclear for me how to transfer this
2012 Mar 14
1
How to use a saved SVM model from e1071
Hello,
I have an SVM model previously calibrated using libsvm R implementation from
the e1071 package.
I would like to use this SVM to predict values, from a Java program.
I first tried to use jlibsvm and the "standard" java implementation of
libsvm, without success.
Thus, I am now considering writing data in files from my Java code, calling
an R program to predict values, then gather
2015 Dec 11
2
SVM hadoop
Hola Mª Luz,
Te cuento un poco mi visión:
Lo primero de todo es tener claro qué quiero hacer exactamente en paralelo,
se me ocurren 3 escenarios:
(1) Aplicar un modelo en este caso SVM sobre unos datos muy grandes y por
eso necesito hadoop/spark
(2) Realizar muchos modelos SVM sobre datos pequeños (por ejemplo uno por
usuario) y por eso necesito hadoop/spark para parelilizar estos procesos
2015 Dec 09
2
SVM hadoop
Buenos días,
alguien sabe si hay alguna manera de implementar una máquina de soporte
vectorial (svm) con R-hadoop??
Mi interés es hacer procesamiento big data con svm. Se que en R, existen
los paquetes {RtextTools} y {e1071} que permiten hacer svm. Pero no estoy
segura de que el algoritmo sea paralelizable, es decir, que pueda correr en
paralelo a través de la plataforma R-hadoop.
Muchas
2002 Aug 20
0
Re: SVM questions
>
> So i guess from your prev. email the svmModel$coefs correspond to the
> "Alpha" .
yes (times the sign of y!).
>
> Why do I see three columns in the coefs?( Is this the number of classes -1
> = Numbe of hyperplanes)
yes, but in a packed format which is not trivial.
I attach some explanation I sent to R-help some time ago (the guy wanted
to write his own
2009 May 11
1
Problems to run SVM regression with e1071
Hi R users,
I'm trying to run a SVM - regression using e1071 package but the function svm() all the time apply a classification method rather than a regression.
svm.m1 <- svm(st ~ ., data = train, cost = 1000, gamma = 1e-03)
Parameters:
SVM-Type: C-classification
SVM-Kernel: radial
cost: 1000
gamma: 0.001
Number of Support Vectors: 209
2006 Feb 02
0
crossvalidation in svm regression in e1071 gives incorre ct results (PR#8554)
1. This is _not_ a bug in R itself. Please don't use R's bug reporting
system for contributed packages.
2. This is _not_ a bug in svm() in `e1071'. I believe you forgot to take
sqrt.
3. You really should use the `tot.MSE' component rather than the mean of
the `MSE' component, but this is only a very small difference.
So, instead of spread[i] <- mean(mysvm$MSE), you
2009 Mar 12
0
e1071 SVM one-classification tune problem
Hello all,
I am using the e1071 SVM with the tune options for classification, which work pretty well, given the examples of using tune.svm function for classification. But I have not found any example to tune the SVM novelty detection (one-classification) parameters (gamma, cost, nu), for example this are some of the options I have tried with no success:
obj<-tune(svm, x,y, type
2017 Sep 02
0
problem in testing data with e1071 package (SVM Multiclass)
Hello all,
this is the first time I'm using R and e1071 package and SVM multiclass
(and I'm not a statistician)! I'm very confused, then. The goal is: I
have a sentence with sunny; it will be classified as "yes" sentence; I
have a sentence with cloud, it will be classified as "maybe"; I have a
sentence with rainy il will be classified as "no".
The
2004 Dec 16
2
reading svm function in e1071
Hi,
If I try to read the codes of functions in e1071 package, it gives me following error message.
>library(e1071)
> svm
function (x, ...)
UseMethod("svm")
<environment: namespace:e1071>
> predict.svm
Error: Object "predict.svm" not found
>
Can someone help me on this how to read the codes of the functions in the e1071 package?
Thanks.
Raj