search for: nnet

...give a clue as to what is going on? Many thanks Francis More information: In the Dom0 I get this when booting the DomU, even with irwpoll in the DomU kernel line xen_pciback: xen-pciback[0000:00:1a.0] IRQ line is not shared with other domains. Turning ISR off Jul 03 11:31:23 antares.fsoft.nnet kernel: irq 18: nobody cared (try booting with the "irqpoll" option) Jul 03 11:31:23 antares.fsoft.nnet kernel: CPU: 0 PID: 0 Comm: swapper/0 Not tainted 3.18.34-20.el7.x86_64 #1 Jul 03 11:31:23 antares.fsoft.nnet kernel: Hardware name: Dell Inc. PowerEdge T430/0975F3, BIOS 1.5.4 10/05/...

Further to my last post, I have removed the xen-pciback module from the Dom0 kernel, and reloaded it as modprobe xen-pciback passthrough=1 I now have the PCI device on the DomU matching the Dom0 Device usb usb1: SerialNumber: 0000:00:1a.0 instead of 0000:00:00.0 However I now have this error ehci_hcd 0000:00:1a.0: Unlink after no-IRQ? Controller is probably using the wrong IRQ. does

HI sorry to be a nuisance to all!!! how can i see the code of a particular function? e.g. nnet just as an example

Hi, I'm currently trying desperately to get the nnet function for training a neural network (with one hidden layer) to perform a regression task. So I run it like the following: trainednet <- nnet(x=traindata, y=trainresponse, size = 30, linout = TRUE, maxit=1000) (where x is a matrix and y a numerical vector consisting of the target values for...

Dear Sir/Madam I have recently started using the nnet package but cannot find any documentation other than the one page titled 'nnet {nnet}' which is replicated several times over the internet and is found in the help file for this package. I would like more information on how to use the package and have searched extensively over the internet...

Hi It clear that to do a classification with svm under 10-fold cross validation one uses svm(Xm, newlabs, type = "C-classification", kernel = "linear",cross = 10) What corresponds to the nnet? nnet(.....,cross=10)? Regards

Hi, I was trying to use the nnet library and am not sure of whats going on. I am calling the nnet function as: n <- nnet(x,y,size=3,subset=sets[[1]], maxit=200) Where x is a 272x4 matrix of observations (examples) and y is a 272x1 matrix of target values. However when I look at nnet$residuals they are off by two orders of ma...

Hi, I just want to point out a discrepancy between the documentation of predict.nnet & the function definition. >?predict.nnet => predict.nnet package:nnet R Documentation Predict New Examples by a Trained Neural Net Description: Predict new examples by a trained neural net. Usage: predict.nnet(object, x, type=c("raw",&...

Dear R people, I want to use the tune.nnet function of e1071 package to tune nnet . I am unable to understand the parameters of tune.nnet from the e1071 pdf document. I have performed nnet on a traindata and want to test it for class prediction with a testdata. I want to know the values of size,decay,range etc. parameters for which the p...

HI, Dear R community, My data set has 2409 variables, the last one is response variable. I have used the nnet after feature selection and works. But this time, I am using nnet to fit a model without feature selection. I got the following error information: > dim(train) [1] 1827 2409 nnet.fit<-nnet(as.factor(out) ~ ., data=train, size=3, rang=0.3, decay=5e-4, maxit=500) # model fitting *Error in...

I was wandering if anybody ever tried to compare the classification accuracy of nnet to other (rpart, tree, bagging) models. From what I know, there is no reason to expect a significant difference in classification accuracy between these models, yet in my particular case I get about 10% error rate for tree, rpart and bagging model and 80% error rate for nnet, applied to the same...

Dear All, I'm learning to train a neural network with my training data by using nnet package, then evaluate it with a evaluation set. My problem here is that, I need the trained network to be used in future, so, what should I store? and How? Any other options other than nnet package? Any example will be highly appreciated! Best, Baoqiang Cao

Hi R help, I run my data in nnet with skip layer, factor response (with 0 & 1 values) and explicitly put softmax=T to compare the result of the default nnet with no softmax specification. I assume this should give me the same result. I got the result the default one, but not the softmax version and I got the error message that...

...putaciones múltiples sobre variables en su mayoría categóricas. El problema está que cuando expresó este comando imp <- mice(dataset,method="polr",maxit=1) donde el dataset es un data.frame me tirá este error : iter imp variable 1 1 pial1a pial2 pial3a pial3b pial3cError en nnet.default(X, Y, w, mask = mask, size = 0, skip = TRUE, softmax = TRUE, : too many (1068) weights -- buscando en foros encontre que debo modificar el nnet, concretamente maxNWts indicando un valor mayor al valor con problema, para modificar eso se me ocurre usar mice.impute.polyreg(dataset x=NULL...

Hello ! I'd like to know to which of the FANN package network corresponds the R nnet network ? In more details, what is the R nnet activation function, what is the training algorithm (rprop, quickprop, ...) ? Also, it seems that the R nnet "decay" parameter in nnet corresponds to the "learning_rate" parameter in FANN. Correct ? Many thanks in advance ! Luc Mou...

Greetings, I am having trouble calculating artificial neural network misclassification errors using errorest() from the ipred package. I have had no problems estimating the values with randomForest() or svm(), but can't seem to get it to work with nnet(). I believe this is due to the output of the predict.nnet() function within cv.factor(). Below is a quick example of the problem I'm experiencing. Any ideas on how to get around it or will it simply not work with nnet()? > library(MASS) > library(nnet) > library(ipred) > data(...

Hi everyone, According to R reference manual, the nnet function uses the BFGS method of optim to optimize the neural network parameters. I would like, when calling the function nnet to tell the optim function not to produce the tracing information on the progress of the optimization, or at least to reduce the frequency of the reports. I tried the follo...

Greetings list, I've just swapped from the "neural" package to the "nnet" package and I've noticed that the training is orders of magnitude faster, and the results are way more accurate. This leads me to wonder, what training algorithm is "nnet" using? Is it a modification on the standard backpropagation? Or a completely different algorithm?...

> nnet.fit<-nnet(as.factor(out) ~ ., data=all_h, size=5, rang=0.3, decay=5e-4, maxit=500) # model fitting > summary(nnet.fit) a 23-5-1 network with 126 weights options were - entropy fitting decay=5e-04 HI, Guys, I can not find the manual to describe how the model is built, is there a more...

Hi, there: I am trying nnet as followed: > mg.nnet<-nnet(x=trn3[,r.v[1:100]], y=trn3[,209], size=5, decay = 5e-4, maxit = 200) # weights: 511 initial value 13822.108453 iter 10 value 7408.169201 iter 20 value 7362.201934 iter 30 value 7361.669408 iter 40 value 7361.294379 iter 50 value 7361.045190 final value 7361.03812...