search for: holdout

...e optimal selection for prediction. So there are two rounds of resampling with the first one taken care of by caret's train function. My question overall is that it seems I must carry the outer resampling plan manually. On another note, I usually get the warning 1: In train.default(colon.x[-holdout, ], outcome[-holdout], method = "pam", : At least one of the class levels are not valid R variables names; This may cause errors if class probabilities are generated because the variables names will be converted to: X1, X2 2: executing %dopar% sequentially: no parallel backend register...

Good day, I'm using a VAR model to forecast sales with some extra variables (google trends data). I have divided my dataset into a trainingset (weekly sales + vars in 2006 and 2007) and a holdout set (2008). It is unclear to me how I should predict the out-of-sample data, because using the predict() function in the vars package seems to estimate my google trends vars as well. However, I want to forecast the sales figures, with knowledge of the actual google trends data. My questions: 1. Ho...

Hello dear R Users, I am working on a dataset of 928 Enterprises, of which are observed 12 different characters. I need to randomly sample, without repetition, 70% of the entreprises, to create a testing set, and let the other 30% of the enterprises be a validating set (holdout validation, I think that is). How do I do that? Of course all the characters of each row must remain together. Also, I am not very familiar with the R-Base language (it is the first time I use it) so if You could also explain to me what every function and argument means, it would be great help to t...

...ge error. I loaded the MASS package and created a model like so: >train <- mod1[mod1$rand < 1.7,] >classify <- mod1[mod1$rand >= 1.7,] >lda_res <- lda(over_win ~ t1_scrd_a + t1_alwd_a, data=train, CV=TRUE) That works, and all is well until I try to do a prediction for the holdouts: >lda_pred <- predict(lda_res, classify)$class Error in predict(lda_res, classify) : no applicable method for "predict" If I try predict.lda specifically I get > lda_pred <- predict.lda(lda_res, classify)$class Error: could not find function "predict.lda" > pre...

...t says: rsq: (regression only) - "pseudo R-squared'': 1 - mse / Var(y). Could someone please explain in somewhat more detail how exactly R^2 is calculated? Is "mse" mean squared error for prediction? Is "mse" an average of mse's for all trees run on out-of-bag holdout samples? In other words - is this R^2 based on out-of-bag samples? Thank you very much for clarification! -- Dimitri Liakhovitski MarketTools, Inc. Dimitri.Liakhovitski at markettools.com

...users to extract the ensembles for a single tree or subset of trees over the forest. The default nodesize for survival and competing risk has been changed to 15. We've added new splitrules "auc" and "entropy" for classification. A new variable importance methodology called Holdout VIMP has been implemented. Here, we exclude a variable from a subset of trees and compare the error rates between those trees in which the variables was included against those in which it was excluded. The key point here is that no permutation of a variable is conducted. See holdout.vimp.rfsrc()...

...users to extract the ensembles for a single tree or subset of trees over the forest. The default nodesize for survival and competing risk has been changed to 15. We've added new splitrules "auc" and "entropy" for classification. A new variable importance methodology called Holdout VIMP has been implemented. Here, we exclude a variable from a subset of trees and compare the error rates between those trees in which the variables was included against those in which it was excluded. The key point here is that no permutation of a variable is conducted. See holdout.vimp.rfsrc()...

...ases where test and validation sets are availiable. For instance, I would like to make one step ahead forecasts on the WWWusage data so I hold out the last 10 observations as the validation set and fit an ARIMA model on the first 90 observations. I then use a for loop to sequentially add 9 of the holdout observations to make 1 step ahead forecasts for the last 10 periods (see example code). In cases where there are relatively few periods I want to forecast for this seems to work fine, however I am working with a rather large validation set and I need to make n step ahead forecasts for many periods...

Got a client that usually uses Outlook I think 2010. This person tends to move their e-mails to certain folers. On Thunderbird, the move shows. Not on Outlook. Any explanation? -- Member - Liberal International This is doctor@@nl2k.ab.ca Ici doctor@@nl2k.ab.ca Yahweh, Queen & country!Never Satan President Republic!Beware AntiChrist rising! https://www.empire.kred/ROOTNK?t=94a1f39b A

...solve my particular problem. Hopefully, a generous fellow R user can help. I have some data that is split into two groups: some "actual" data, and some simulated data, generated from several different models. The actual data come from two different datasets (calibration and holdout), and the simulations were calibrated on each data set under the various models. What I want to do is create a boxplot on the simulated data, and superimpose a line representing the actual data. This plot would condition on dataset and model. While the simulated data various across model...

...to certain folers. On Thunderbird, the move shows. > Not on Outlook. > > Any explanation? Since the move works fine in Thunderbrd (and I assume any other client will see the same), the problem is with Outlook 2010. Perhaps a gentle reminder that it is currently 2020? I moved the last holdout client off 2010 about 2 or 3 yers ago after having many many problems with it that could not be easily fixed because the software was no longer supported and I pointed out they were sending more money paying me to try to fix it than it would cost them to pay for Office 365 (small business, obviousl...

> From: Wensui Liu <liuwensui at gmail.com> > Just curious how xlispstat is used in the industry and what's it strengthen > compared with other computing languages such as R or matlab? Almost not at all, though there are a few holdouts. On a related note, I've been doing some interesting things with a branch of LispStat for CommonLisp. It'll be more interesting when R gets embedded (now it's back on topic). Rumor has it that R is embedded within SBCL, which makes for an interesting distributed computing environmen...

Hi listers, I'm a 1.4 holdout who uses mostly Suse platforms. I bit the bullet and installed a Centos box to get Lumenvox up and running, but now see this "new" offering of Vestec that supports OpenSuse and Windows in addition to the Platforms supported by Lumenvox. Anybody out there working with Vestec that can giv...

Hi! I am working on scorecard model and I have arrived at the regression equation. I have used logistic regression using R. My question is how do I validate this model? I do have hold out sample of 5000 customers. Please guide me. Problem is I had never used Logistic regression earlier neither I am used to credit scoring models. Thanks in advance Maithili

On Mon, Sep 04, 2023 at 06:59:15PM +0000, Tage Johansson wrote: > > > > + // can be both readable and writable, but we survive just fine > > > + // if we only see one direction even when both are available. > > > + poll.registry().register( > > > + &mut SourceFd(&fd), > > > + Token(0), > >

CRAN (and crantastic) updates this week New packages ------------ * bdoc (1.0) Michael Anderson http://crantastic.org/packages/bdoc This package contains a function that will classify DNA barcodes as well as a few test and reference data sets. * bdsmatrix (1.0) Terry Therneau http://crantastic.org/packages/bdsmatrix This is a special case of sparse matrices, used by coxme and

Must have bolluxed something up in the compile environment - that or http://www.mindrot.org/openssh_snap/openssh-SNAP-20140828.tar.gz had a configure tweak that fixed it. All systems tested now build and pass all tests. That said - the stupid race condition in that one test is cropping up sporadically still - I think it's related to the load (or lack thereof) on the VM host. With, of

Hi All, I am trying to learn Neural Networks. I found that R has packages which can help build Neural Nets - the popular one being AMORE package. Is there any book / resource available which guides us in this subject using the AMORE package? Any help will be much appreciated. Thanks, Indrajit

Hello fans of the auto keyword! We now have a policy on how LLVM toolchains get updated <https://reviews.llvm.org/rL351765>! Let’s put that policy to good use, and talk about how we’ll move all monorepo projects past C++11. Previous Discussions LLVM dev meeting 2018 BoF "Migrating to C++14, and beyond! <http://llvm.org/devmtg/2018-10/talk-abstracts.html#bof3>" A Short