similar to: PLS component selection for GPLS question

Displaying 20 results from an estimated 100 matches similar to: "PLS component selection for GPLS question"

2008 Apr 23
1
significant variables in GPLS ?
Hello, I am using the gpls package for modelling vegetation classes. My problem is that I now want to know which input variables are significant for the modelling of the classes to recalculate the equation again with just the selected variables. I think I can analyse the significance of the variables via their weights. I used the "gpls1a" term for two group classification. Here my
2010 Apr 25
1
function pointer question
Hello, I have the following function that receives a "function pointer" formal parameter name "fnc": loocv <- function(data, fnc) { n <- length(data.x) score <- 0 for (i in 1:n) { x_i <- data.x[-i] y_i <- data.y[-i] yhat <- fnc(x=x_i,y=y_i) score <- score + (y_i - yhat)^2 } score <- score/n
2012 May 15
1
caret: Error when using rpart and CV != LOOCV
Hy, I got the following problem when trying to build a rpart model and using everything but LOOCV. Originally, I wanted to used k-fold partitioning, but every partitioning except LOOCV throws the following warning: ---- Warning message: In nominalTrainWorkflow(dat = trainData, info = trainInfo, method = method, : There were missing values in resampled performance measures. ----- Below are some
2005 Jul 25
5
passing formula arguments cv.glm
I am trying to write a wrapper for the last example in help(cv.glm) that deals with leave-one-out-cross-validation (LOOCV) for a logistic model. This wrapper will be used as part of a bigger program. Here is my wrapper funtion : logistic.LOOCV.err <- function( formu=NULL, data=NULL ){ cost.fn <- function(cl, pred) mean( abs(cl-pred) > 0.5 ) glmfit <- glm(
2004 Nov 24
2
LDA with previous PCA for dimensionality reduction
Dear all, not really a R question but: If I want to check for the classification accuracy of a LDA with previous PCA for dimensionality reduction by means of the LOOCV method: Is it ok to do the PCA on the WHOLE dataset ONCE and then run the LDA with the CV option set to TRUE (runs LOOCV) -- OR-- do I need - to compute for each 'test-bag' (the n-1 observations) a PCA
2013 Mar 23
1
LOOCV over SVM,KNN
Good afternoon. I would like to know if there is any function in R to do LOOCV with these classifiers: 1)SVM 2)Neural Networks 3)C4.5 ( J48) 4)KNN Thanks a lot! [[alternative HTML version deleted]]
2012 Oct 03
2
Error in if (any(ch)) { : missing value where TRUE/FALSE needed
Can someone please help with the error message below? thanks! Start: AIC=-Inf value ~ 1 + Core_CPI__ + GDP_change + Unemployment + housing + interest + S_P + d1 + d2 + d3 Error in if (any(ch)) { : missing value where TRUE/FALSE needed In addition: Warning message: attempting model selection on an essentially perfect fit is nonsense
2008 Nov 14
0
Cross-validation
Hi, I was trying to do cross-validation using the crossval function (bootstrap package), with the following code: --------------------------------------------------------------------------------------------------------- theta.fit <- function(x,y){ model <- svm(x,y,kernel = "linear") } theta.predict <- function(fit,x){ prediction <- predict(fit,x)
2008 Jun 05
1
Re: [Resolved] Wine 0.9.46 and Warcraft 3 Reign of Chaos
stimpak wrote: > idont forget to run it with a -opengl flag Thank you so very much!!!! That let me play warcraft 3 on my laptop with linux and Intel 945gm graphik card on ubuntu 8.04, quite well! Thank you! I searched a while, but can't find anything, that helps, now only the -opengl flag was missing.. [Rolling Eyes] great. Maybe that should be added in the APPDB warcraft 3 entry...
2012 Oct 09
1
why does R stepAIC keep unsignificant variables?
Ran a bunch of variables in R and the final result of StepAIC is as below: Why are the first 5 variables kept in the stepwise result?? Are the last 4 variables finally chosen after Stepwise? Thanks Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.315e-01 2.687e-01 0.490 0.63611 Core_CPI__ 1.290e-02 7.496e-03 1.721 0.11927 GDP_change -3.482e-03 2.075e-03 -1.678 0.12767
2017 Dec 02
0
How can you find the optimal number of values to randomly sample to optimize random forest classification without trial and error?
I have data set up like the following: control1 <- sample(1:75, 3947398, replace=TRUE) control2 <- sample(1:75, 28793, replace=TRUE) control3 <- sample(1:100, 392733, replace=TRUE) control4 <- sample(1:75, 858383, replace=TRUE) patient1 <- sample(1:100, 28048, replace=TRUE) patient2 <- sample(1:50, 80400, replace=TRUE) patient3 <- sample(1:100, 48239, replace=TRUE) control
2008 Sep 06
0
New caret packages
New major versions of the caret packages (caret 3.37, caretLSF 1.23 and caretNWS 0.23) have been uploaded to CRAN. caret is a package for building and evaluating a wide variety of predictive models. There are functions for pre-processing, tuning models using resampling, visualizing the results, calculating performance and estimating variable importance. caretNWS and caretLSF are two parallel
2008 Sep 06
0
New caret packages
New major versions of the caret packages (caret 3.37, caretLSF 1.23 and caretNWS 0.23) have been uploaded to CRAN. caret is a package for building and evaluating a wide variety of predictive models. There are functions for pre-processing, tuning models using resampling, visualizing the results, calculating performance and estimating variable importance. caretNWS and caretLSF are two parallel
2004 Aug 23
0
A troubled state of freedom: generalized linear models wh ere number of parameters > number of samples
Check out the gpls package on CRAN. HTH, Andy > From: Min-Han Tan > > Good morning, > > Thank you all for your help so far. I really appreciate it. > > The crux of my problem is that I am generating a generalized linear > model with 1 dependent variable, approximately 50 training samples and > 100 parameters (gene levels). > > Essentially, if I have 100
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
2004 May 17
0
Bioconductor 1.4 released
Greetings! The Bioconductor core group would like to announce the 5th release of Bioconductor, version 1.4. There are many new packages as well as several major upgrades and fixes in older packages, and users are encouraged to upgrade existing tools and check out the new packages. Release 1.4 is intended to be operated with R version 1.9.x, which can be obtained at CRAN
2012 Mar 14
2
Maximization problem in the optim function
Dear R Users I am maximizing a user defined log likelihood function. It includes variance parameter (sigma). I used R function optim with BFGS maximization method. However, it stops before the solution saying ?sqrt(sigma): NaNs produced? Could anybody know a proper transformation for sigma which can be passed in the function? For the correlation parameter I used Fishers? transformation so it
2008 Feb 27
7
Cross Validation
Hello, How can I do a cross validation in R? Thank You!
2013 Oct 18
0
Logistic regression over LOOCV
Hello all. I have this code: myLOOCV <- function(myformula, data) { Y <- all.vars(myformula)[1] Scores<- numeric(length(data[,1])) for (i in 1:length(data[,1])) { train <- data[-i,] test <- data[i,] myModel <- lrm(myformula, train) Scores[i] <- predict(myModel, test,type="mean") }
2004 Feb 25
2
LOOCV using R
Can someone help me with performing leave-out-one cross validation using R (model built is a Cox model)? Thanks. --------------------------------------------- David Verbel, MPH Senior Biostatistician Aureon Biosciences 28 Wells Avenue Yonkers, NY 10701 Phone: (914) 377-4021 Fax: (914) 377-4001 --------------------------------------------- [[alternative HTML version deleted]]