similar to: Neural Net forecasting

Deall all, We need to perform a statistical analysis of a large database (40,000 entries with approximately 500 fields in each entry) currently handled in Oracle. The data contains categorical variables only. At the current stage we suggest classification and clustering analysis. We are planning to perform the analysis in R and would be very grateful for any

Hi All, I am interested in learning about people's experience with R training or courses. What worked, what didn't? What do you recommend? Also, if there any groups or individuals that have and can offer R training courses, please contact me directly. I would like to learn about your services. Thanks for your input and help. Please feel free to contact me directly. Russ

Hi r-people :) I'm sorry to disturb but I must admit that I know amazingly little about R and similar statistics-packages/languages and I'm kind of lost on where to start. I'm currently working on a datacollection framework for postgresql (The db doesn't really matter except that I hope to use PL/R) and I would like to be able to predict future values preferable 1 day or more

I am new to R and use nnetTs - calls. If a time series of let's say 80000 Datapoints and did call nnetTs I want make a new net for the old ponts plus the next 1000 points (81000 datapoints total) what would again cost much calculation time. So I want to pre-init the new net with the former wonnen net to reduce the necessary iteration numbers. Is thee a possibility to do that and how? i.e.:

Dear R-user, I wish to know if someone is using R as concern Datamining or KDD (Knowledge Discovery in Database) and if already exists a R package specialized in this kind of analysis. I found this contributes on the R web site: [20] Diego Kuonen. Introduction au data mining avec R : vers la reconqu??te du `knowledge discovery in databases' par les statisticiens. Bulletin of the Swiss

Hello all, Im just beggining using R. I have read a couple of introductory documents but they are very general. Is there a document focused on classification? (this is what Ill be using R for). Examples would be just fine. Thanks in advance, Ulises

Dear all, I have just found a 'good' tutorial R for datamining. I think it should be on the contributed docs. http://cran.r-project.org/other-docs.html Here is the link http://www.liaad.up.pt/~ltorgo/DataMiningWithR/ What do you think? Kind regards Christophe -- Christophe Dutang Ph. D. student at ISFA, Lyon, France website: http://dutangc.free.fr

I'm reading Torgo (2010) *Data Mining with R*<http://www.liaad.up.pt/~ltorgo/DataMiningWithR/code.html>in preparation for a class I'll be teaching next quarter. Here's an example that is very non-functional. > pH <- c(4.5,7,7.3,8.2,6.3) > names(pH) <- c('area1','area2','mud','dam','middle') > pH area1 area2 mud dam

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 everyone, I'm a graduate student of engineering, lately introduced with R. and using R for my project and thesis. I'm trying to use R for implementing a neural network regression model and apply it to my database. I found three R packages ("AMORE" , "grnnR" , "neural") in R website, but their manuals are not really user-friendly in my idea. I was wondering

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.

I've got a PhD student starting this year. She'll be working on data mining. She has asked for a reading list while she's still in her home country, which is a really good sign. Her cosupervisor and I don't (think we) have any problem with choosing things that are specifically about data mining, but there are some statistical ideas (sampling, exploratory-vs-confirmatory,

Hi all, I am trying to develop a neural network with single target variable and 5 input variables to predict the importance of input variables using R. I used the packages nnet and RSNNS. But unfortunately I could not interpret the out put properly and the documentation of that packages also not giving proper direction. Please help me to find a good package with a proper documentation for neural

Hi. I started with a file which was a sparse 982x923 matrix and where the last column was a variable to be predicted. I did principle component analysis on it and arrived at a new 982x923 matrix. Then I ran the code below to get a neural network using nnet and then wanted to get a confusion matrix or at least know how accurate the neural net was. I used the first 22 principle components only for

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 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

R people, I need to know if is possible to make data mining with R. If so, is there any manual or somewhere/one to consult about that. Thank you very much Adri?n

Hi, I am trying to build a VERY basic neural network as a practice before hopefully increasing my scope. To do so, I have been using package "neural" and the MLP related functions (mlp and mlptrain) within that package. So far, I have created a basic network, but I have been unable to change the default activation function. If someone has a suggestion, please advise. The goal of the

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

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,