Displaying 20 results from an estimated 200 matches similar to: "Help for using nnet in R for NN training and testing"
2007 Jan 22
0
Recursive-SVM (R-SVM)
I am trying to implement a simple r-svm example using the iris data (only two of the classes are taken and data is within the code). I am running into some errors. I am not an expert on svm's. If any one has used it, I would appreciate their help. I am appending the code below.
Thanks../Murli
#######################################################
### R-code for R-SVM
### use leave-one-out
2018 Feb 19
0
questions regarding the svmpath package (functions svmpath and predict)
Hello,
I have two questions.
The svmpath package provides a svmpath function:
---
fit <- svmpath(xtrain, ytrain, kernel.function = radial.kernel, param.kernel = 0.8)
---
1) How to get the optimal lambda value out of this result?
The svmpath package also provides a predict function:
---
ytest <- predict(fit, xtest)
---
How to get a score (or a probability of belonging to one of the two
2007 Oct 23
1
Compute R2 and Q2 in PLS with pls.pcr package
Dear list
I am using the mvr function of the package pls.pcr to compute PLS
resgression using a X matrix of gene expression variables and a Y matrix
of medical varaibles.
I would like to obtain the R2 (sum of squares captured by the model) and
Q2 (proportion of total sum of squares captured in leave-one-out cross
validation) of the model.
I am not sure if there are specific slots in the
2004 Nov 15
0
how to obtain predicted labels for test data using "kernelpls"
Dear members,
My name is Seungho Huh. I am a statistician who tries to use the Kernel
PLS method in a classification problem. I am sending this email to ask
you something about the "kernelpls" function in R (pls.pcr package).
I would like to obtain the predicted Y values for test data, using the
Kernel PLS method. Let's take the example in the R help:
> data(NIR)
>
2009 Oct 14
0
Confusion matrix from cross validation in R:
Hey!
How do I get the confusion matrix after performing 10-fold cross validation
from SVM in R?
When I try to print it, I get the confusion matrix without cross validation.
I need to compute PPV. Should I report PPV without CV and total accuracy
with CV?
I am confused.
> svmtrain <- svm(xtrain,ytrain,kernel="sigmoid",cross=10)
> pred <- predict(svmtrain, xtrain)
>
2004 Nov 15
0
how to obtain predicted labels for test data using "kerne lpls"
You need to do some extra work if you want to do classification with a
regression method. One simple way to do classification with PLS is to code
the classes as 0s and 1s (assuming there are only two classes) or -1s and
1s, fit the model, then threshold the prediction; e.g., those with predicted
values < 0.5 (in the 0/1 coding) get labeled as 0s. There's a predict()
method for mvr
2012 Sep 13
0
I need help for svm package kernlab in R
I use the svm package kernlab .I have two question.
In R
library(kernlab)
m=ksvm(xtrain,ytrain,type="C-svc",kernel=custom function, C=10)
alpha(m)
alphaindex(m)
I can get alpha value and alpha index about package.
1.
Assumption that number of sample are 20.
number of support vectors are 15.
then rest 5`s alphas are 0?
2. I want use kernelMatrix
xtrain=as.matrix(xtrain)
2011 May 24
1
seeking help on using LARS package
Hi,
I am writing to seek some guidance regarding using Lasso regression with the
R package LARS. I have introductory statistics background but I am trying to
learn more. Right now I am trying to duplicate the results in a paper for
shRNA prediction "An accurate and interpretable model for siRNA efficacy
prediction, Jean-Philippe Vert et. al, Bioinformatics" for a Bioinformatics
project
2008 Feb 05
0
Uninformative error msgs w/ svm.default - Error in svm.default ... y must be a vector or a factor -
Hello,
I'm using recursive SVM script (rSVM - http://www.stanford.edu/group/wonglab/RSVMpage/R-SVM.html ) on some microarray data. The data to be input are log2, as numeric matrix w/ attributes --
str(svm_num_mat)
num [1:10, 1:12340] 13.1 13.1 13.1 13.1 13.0 ...
- attr(*, "dimnames")=List of 2
..$ : chr [1:10] "rma_log2_con_sample_1"
2012 Aug 27
0
kernlab`s custom kernel of ksvm freeze
Hello, together
I'm trying to use user defined kernel. I know that kernlab offer user
defined kernel(custom kernel functions) in R.
I used data spam including package kernlab.
(number of variables=58 number of examples =4061)
i'm user defined kernel's form,
kp=function(d,e){
as=v*d
bs=v*e
cs=as-bs
cs=as.matrix(cs)
exp(-(norm(cs,"F")^2)/2)
}
2005 Nov 25
3
obtaining a ROC curve
Hello,
I have a classification tree. I want to obtain a ROC curve for this test. What is the easiest way to obtain one?
-Anjali
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2012 Nov 30
1
Baffled with as.matrix
I'm puzzled by as.matrix. It appears to work differently for Surv objects.
Here is a session from my computer:
tmt% R --vanilla
> library(survival)
Loading required package: splines
> ytest <- Surv(1:3, c(1,0,1))
> is.matrix(ytest)
>[1] TRUE
> attr(ytest, 'type')
[1] "right"
> attr(as.matrix(ytest), 'type')
[1] "right"
>
2001 Feb 21
1
glm predict problem with type = "response"
The standard errors produced by predict.glm with type = "response" seem
wrong. Here is an example using R 1.2 windows version along with the same
problem in Splus. The standard errors for type = "link" are the same in
both systems.
R1.2> set.seed(10)
R1.2> ytest <- 100*.95^(0:9) + rnorm(10,sd = 5)
R1.2> ytest
[1] 103.96964 97.60590 88.43220 85.90504
2008 Jun 15
1
randomForest, 'No forest component...' error while calling Predict()
Dear R-users,
While making a prediction using the randomForest function (package
randomForest) I'm getting the following error message:
"Error in predict.randomForest(model, newdata = CV) : No forest component
in the object"
Here's my complete code. For reproducing this task, please find my 2 data
sets attached ( http://www.nabble.com/file/p17855119/data.rar data.rar ).
2005 Jun 23
1
errorest
Hi,
I am using errorest function from ipred package.
I am hoping to perform "bootstrap 0.632+" and "bootstrap leave one out".
According to the manual page for errorest, i use the following command:
ce632[i]<-errorest(ytrain ~., data=mydata, model=lda,
estimator=c("boot","632plus"), predict=mypredict.lda)$error
It didn't work. I then tried the
2004 Jan 20
1
random forest question
Hi,
here are three results of random forest (version 4.0-1).
The results seem to be more or less the same which is strange because I
changed the classwt.
I hoped that for example classwt=c(0.45,0.1,0.45) would result in fewer
cases classified as class 2. Did I understand something wrong?
Christian
x1rf <- randomForest(x=as.data.frame(mfilters[cvtrain,]),
2004 Apr 15
7
all(logical(0)) and any(logical(0))
Dear R-help,
I was bitten by the behavior of all() when given logical(0): It is TRUE!
(And any(logical(0)) is FALSE.) Wouldn't it be better to return logical(0)
in both cases?
The problem surfaced because some un-named individual called randomForest(x,
y, xtest, ytest,...), and gave y as a two-level factor, but ytest as just
numeric vector. I thought I check for that in my code by testing
2012 Oct 22
1
random forest
Hi all,
Can some one tell me the difference between the following two formulas?
1. epiG.rf <-randomForest(gamma~.,data=data, na.action = na.fail,ntree =
300,xtest = NULL, ytest = NULL,replace = T, proximity =F)
2.epiG.rf <-randomForest(gamma~.,data=data, na.action = na.fail,ntree =
300,xtest = NULL, ytest = NULL,replace = T, proximity =F)
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2012 Mar 08
2
Regarding randomForest regression
Sir,
This query is related to randomForest regression using R.
I have a dataset called qsar.arff which I use as my training set and
then I run the following function -
rf=randomForest(x=train,y=trainy,xtest=train,ytest=trainy,ntree=500)
where train is a matrix of predictors without the column to be
predicted(the target column), trainy is the target column.I feed the same
data
2009 Apr 04
1
error in trmesh (alphahull package)
Hello R community,
I have cross-posted with r-sig-geo as this issue could fall under either
interest group I believe.
I just came accross the alphahull package and am very pleased I may not
need to use CGAL anymore for this purpose. However, I am having a
problem computing alpha shapes with my point data, and it seems to have
to do with the spatial configuration of my points (which form