search for: neuralnet

Estimados Tengo un problema, R se cuelga (cierra, aborta, etc.) al usar códigos de neuralnet. Copio un ejemplo cualquiera para preguntar si a otros les pasa lo mismo o es un problema puntual en mi computadora (uso R revolution win 10). # install, load package install.packages(NeuralNetTools) library(NeuralNetTools) # create model library(neuralnet) AND <- c(rep(0, 7), 1) OR <- c(0,...

I require some help in debugging this code  library(neuralnet) ir<-read.table(file="iris_data.txt",header=TRUE,row.names=NULL) ir1 <- data.frame(ir[1:100,2:6]) ir2 <- data.frame(ifelse(ir1$Species=="setosa",1,ifelse(ir1$Species=="versicolor",0,""))) colnames(ir2)<-("Output") ir3 <- data.frame(rb...

Muchas gracias Instale R desde CRAN y ejecutar version en R y R revolution, informa lo mismo, pero en el segundo neuralnet se cuelga, paso una captura de pantalla (Rstudio bajo r revolution también tiene problemas, no con R desde CRAN). Javier Rubén Marcuzzi Técnico en Industrias Lácteas Veterinario De: juan(uned) Enviado: martes, 3 de noviembre de 2015 12:48 Para: r-help-es en r-project.org Asunto: Re: [R-es] Pr...

Hola a todos, en primer lugar quería agradecer la ayuda recibida desde el foro con respecto a la creación de una red neuronal. Estoy utilizando el paquete Neuralnet, que me parece que es bastante bueno, pero tengo el problema que soy incapaz de hacer las predicciones del modelo. Sé que se hace con el comando "compute", pero no encuentro ningún ejemplo de cómo hacerlo. ¿Alguien me puede ayudar? La red neural que creo la hago con el siguiente código:...

...third column to the output neuron of the weight. constant.weights: A vector specifying the values of the weights that are excluded from the training process and treated as fix. Please refer to the following example: Not using exclude and constant.weights (all weights are trained): > nn <- neuralnet(Species == "setosa" ~ Petal.Length + Petal.Width, iris, linear.output = FALSE) > > nn$weights [[1]] [[1]][[1]] [,1] [1,] 6.513239 [2,] -0.815920 [3,] -5.859802 [[1]][[2]] [,1] [1,] -4.597934 [2,] 9.179436 Using exclude (2 weights are excluded --> NA): > nn <- neuralnet(Sp...

Hello List ! I'm a bright new R user, and I encounter a problem when trying to use the neuralnet package. I have a training set with 8 inputs, and there are 3 outputs (I need 3 distinct neurones as output). Although I read the examples, and the package article, I don't know how to tell R there are 3 outputs (3 outputs neurones). Here is my actual code : # All = input data All <- read...

Hi R, Here's a question/problem on the 'neuralnet' package for neural networks. I have more than 50 factors in each of my independent variables. When I apply the command 'neuralnet', I get the below warning message, > net.sum <- neuralnet( Sum~Var1+Var2+Var3, b, hidden=0,linear.output=TRUE) Warning message: 'prediction...

Hi, I am having difficulty in training a neural network using the package "neuralnet". My neural network has 2 input neurons (covariates), 1 hidden layer with 2 hidden neurons and 2 output neurons (responses). I am training my neural network with a dataset that has been transformed so that each column is of type "numeric". The difficulty I am facing is that the res...

Dear all, I have a variable that I would like also to use it as a string. The reasons is that I want to collect results from different function to one table.. So when I use the  colnames(mymatrix) <-c(function1.function2,function3) the function1, function2, function3 to be "converted" to simple strings so as  colnames(mymatrix)

Good Morning, I am using the neuralnet package in R, and am able to produce some basic neural nets, and use the output. I would like to exclude some of the weights and biases from the iteration process and fix their values. However I do not seem to be able to correctly define the exclude and constant.weights vectors. Question: Can s...

Hello I am new to R and wonder whether someone out there could send me an example on how to use the package neuralnet to fit a model to data, following the usual procedure, that is, fitting the model using the training set and then using the validation set to check the model. Moreover, the neural net model is recursive (uses its own output values)-> infinite steps ahead prediction. Many thanks Ed

good night Again I ask for help to the community, as I am new at this, I have some basic questions. I am looking for packages on neural networks and so you can search found these two that I think are the most used, neuralnet, nnet. So you can test, and correct me if I'm wrong the neuralnet only accepts as input values ??nomer, did a little test data (iris) library (neuralnet) Species.numeric <- as.numeric (iris $ Species) iris.df <- data.frame (iris, Species.numeric) net <- neuralnet (~ Species.num...

good night Again I ask for help to the community, as I am new at this, I have some basic questions. I am looking for packages on neural networks and so you can search found these two that I think are the most used, neuralnet, nnet. So you can test, and correct me if I'm wrong the neuralnet only accepts as input values ??nomer, did a little test data (iris) library (neuralnet) Species.numeric <- as.numeric (iris $ Species) iris.df <- data.frame (iris, Species.numeric) net <- neuralnet (~ Speci...

...C3=BCnther?= <guenther at leibniz-bips.de> To: "r-help at r-project.org" <r-help at r-project.org> Cc: William Michels <wjm1 at caa.columbia.edu>, "smm at posteo.org" <smm at posteo.org> Subject: Re: [R] Fwd: Help using the exclude option in the neuralnet package Message-ID: <957726669.124476.1602484424752 at srvmail.bips.eu> Content-Type: text/plain; charset="utf-8" Dear all, the exclude and constant.weights options are used as follows: exclude: A matrix with n rows and 3 columns will exclude n weights. The the first colu...

Hi I would like to know how I can change the name of a model for each trainning cycle of a model. I work with the RSNNS package and to build a neural network, I used : for (i in 5:30) .... model_ANN <- mlp(X, Y, size=n,....) # where size is the number of neurons in the hidden layer but I need to save each time that the model that is build (the end of each cycle), e.g., when i = 5, I need to

...nther at leibniz-bips.de> > To: "r-help at r-project.org" <r-help at r-project.org> > Cc: William Michels <wjm1 at caa.columbia.edu>, "smm at posteo.org" > <smm at posteo.org> > Subject: Re: [R] Fwd: Help using the exclude option in the neuralnet > package > Message-ID: <957726669.124476.1602484424752 at srvmail.bips.eu> > Content-Type: text/plain; charset="utf-8" > > Dear all, > > the exclude and constant.weights options are used as follows: > > exclude: A matrix with n rows and 3 columns...

I didn't get any responses to this question on stats.SE: - http://stats.stackexchange.com/questions/34415/optimization-of-models-ann-radial-basis-etc-in-r-to-target-predictor-levels What I'm looking for, using neuralnet as an example, is how to guide a model toward an output profile once the model is trained. For example: model1 <- neuralnet(formula=out1 ~ intput1 + input2 + input3 + input4, data=train, hidden=6, threshold=0.05, linear.output=TRUE) model2 <- neuralnet(formula=out2 ~ intp...

Estimados Hace un tiempo pregunte por un problema con neuralnet, hoy instale R desde https://mran.revolutionanalytics.com/ y el problema anterior fue solucionado por sus desarrolladores, pero me asombre por un cambio en la velocidad (no use un test con muchos datos como para ser objetivos pero la experiencia de usuario es fluida). Simplemente comparto el link...

...dad. Mi problema, es que estoy intentando hacer una comparación entre tres sistemas de predicción: una regresión logística, un árbol de clasificación y una red neuronal. De momento, he podido hacer las comparaciones con los dos primeros sistemas, pero mi problema es la red. He utilizado el paquete neuralnet y logro crear la red, pero ahora no sé cómo hacer que calcule los valores esperados y luego hacer la curva roc. Ahora estoy utilizando todos los datos, no he dividido la muestra en entrenamiento y prueba, pero luego lo haré. ¿Me podéis indicar cómo solventar este problema? Muchas gracias a todos

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 into this project, I'd appreciate it. Thanks! [[alternative HTML...