similar to: Neural Networks in R - Query

I am interested in Neural network models in R. Is there any reference material/tutorial which i can use. Regards, ____________________________________________________________________________________ TV dinner still cooling? Check out "Tonight's Picks" on Yahoo! TV.

Hi, I am would like to ask few questions. I am trying to forecast hourly electricity prices by 24 hours ahead. I have hourly data starting from 2015*12*18 to 2017-10-24 and I have defined the data as time series as written in the code below. Then I am trying do neural network with 23 non-seasonal dummies and 1 seasonal dummy. But I don?t know whether training set is enough.( Guess it is 50

Hi, I am starting to play around with neural networks and noticed that there are several packages on the CRAN website for neural networks (AMORE, grnnR, neural, neuralnet, maybe more if I missed them). Are any of these packages more well-suited for newbies to neural networks? Are there any relative strengths / weaknesses to the different implementations? If anyone has any advice before I dive

Hi folks, I want to apply a neural network to a data set to classify the observations in the different classes from a concrete response variable. The idea is to prove different models from network modifying the number of neurons of the hidden layer to control overfitting. But, to select the best model how I can choose the relevant variables? How I can eliminate those that are not significant for

I want to create a neural network, and then everytime it receives new data, instead of creating a new nnet, i want to use a backpropagation algorithm to adjust the weights in the already created nn. I'm using nnet package, I know that nn$wts gives the weights, but I cant find out which weights belong to which conections so I could implement the backpropagation algorithm myself. But if anyone

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. Is NN for R for Win available? It seemes that there's no NN package in contributed ones. -------------- next part -------------- An HTML attachment was scrubbed... URL: https://stat.ethz.ch/pipermail/r-help/attachments/20010310/6a58939c/attachment.html

hi all , has anyone tried to predict a univariate time series by a neural networks packages ? please help me in this problem . I am new in R and I did not found any document that explains this problem. thanks in advance David [[alternative HTML version deleted]]

Hello All! I am training to train a NN with function train() after splitting data with the function splitForTrainingAndTest(). The split is ok (checked it), but when I get a try on training I get this message: Error in UseMethod("train") : no applicable method for 'train' applied to an object of class "c('double', 'numeric')" The input data are

People, I thought I needed to have some familiarity with NNs for some of my current (non-profit, brain-related) projects so I started looking at various programming environments including R and I got this working: http://gekkoquant.com/2012/05/26/neural-networks-with-r-simple-example however I needed pictures to help understand what was going on and then I found this:

Hello, I use nnet to do prediction for a continuous variable. after that, I calculate correlation coefficient between predicted value and real observation. I run my code(see following) several time, but I get different correlation coefficient each time. Anyone know why? In addition, How to calculate prediction accuracy for prediction of continuous variable? Aimin thanks, > m.nn.omega

Sorry for these multiple postings. I solved the problem using na.omit() to drop records with missing values for the time being. I will worry about imputation, etc. later. I calculated the sum of squared errors for 3 models, linear regression, neural networks, and support vector machines. This is the first run. Without doing any parameter tuning on the SVM or playing around with the number of

Hi! I am studying to use some R libraries which are applied for working with artificial neural neworks (amore, nnet). Can you recommend some useful, reliable and easy to get example data to use in R for creating and testing a neural network? __________________________________________________________________ Make your browsing faster, safer, and easier with the new Internet

Hi all, I'm running a monte carlo test of a neural network tool I've developed, and it looks like it's going to take a very long time if I run it in R so I'm interested in translating my code (included below) into something faster like Fortran (which I'll have to learn from scratch). However, as you'll see my code loads the nnet library and uses it quite a bit, and I

Hello, I have a trained Back Propagation Neural Network model in weka. I would like to re-evaluate the NN using R with a given input. How can I do this? I could not find an example of RWeca that applies to NN Thanks, Rui

Hi, I'm working on a classification problem and one of the methods I'd like to use are neural networks. I've been using nnet to build a classification network. However I would like to have the probabilities associated with the prediction. Are there any implementations of probabilistic neural networks available in R? thanks,

Hello! We are a group of three students at Bielefeld University currently working on a statistical projects about neural networks. Within the framework of this project we are supposed to use the nnet-function in R and explain how it works. Since anyone of us has much experience in using R we hoped to find some information on your homepage. Unfortunatelly, we haven't been very successfull so

Hi all I have a question about correct usage of persp(). I have a simple neural net-based XOR example, as follows: library(nnet) xor.data <- data.frame(cbind(expand.grid(c(0,1),c(0,1)), c(0,1,1,0))) names(xor.data) <- c("x","y","o") xor.nn <- nnet(o ~ x + y, data=xor.data, linout=FALSE, size=1) # Create an (x.y) surface and predict over all points d <-

Hi all gurus, I have a few general questions about using neural networks function, i.e. the nnet function. I'm new to this function and still exploring it. So please kindly bear with me. Here are my questions. 1. Is there anyway that I can specify my own objective or loss function for my neural networks? I see that by arguments that we can pass into the networks, we have either square loss

Hi, a few month ago, I tried to install zaptel for my Beronet BN8S0 pci card... I gave up and took hfcmulti/lcr. Now dahdi (2.2.1.1) seems to support the card and I'm very interested to get it to work. But how to get rid of these annoying qozap driver? bishop dahdi # lspci -v -nn -s 01:00.0 01:00.0 ISDN controller [0204]: Cologne Chip Designs GmbH ISDN network Controller [HFC-8S]