search for: neuron

...but just recently It's been giving me a few problem, I haven't tracked down exactly what causes the problem yet (I'm using Apple Mail on OS X 10.2.6) but after a good mail session it keep trying to log in over and over again.. Looking the the log file I find this... Jun 20 15:38:02 neuron imap-login: Login: sgare [IP REMOVED] Jun 20 15:38:02 neuron imap(sgare): file imap-bodystructure.c: line 263 (part_parse_headers): assertion failed: (part->physical_pos >= input->v_offset - start_offset) Jun 20 15:38:02 neuron dovecot: child 6329 (imap) killed with signal 6 Jun 20 15:38...

...ints. With many thanks, Greg Jefferis. [1] http://github.com/jefferislab/nat.nblast https://cran.r-project.org/package=nat.nblast [2] @article{Costa:2016aa, Author = {Costa, Marta and Manton, James D and Ostrovsky, Aaron D and Prohaska, Steffen and Jefferis, Gregory S X E}, Doi = {10.1016/j.neuron.2016.06.012}, Journal = {Neuron}, Month = {Jul}, Number = {2}, Pages = {293-311}, Title = {NBLAST: Rapid, Sensitive Comparison of Neuronal Structure and Construction of Neuron Family Databases}, Volume = {91}, Year = {2016}} [3] https://rdrr.io/github/ropensci/RefManageR/man/toBiblatex.htm...

...person(given = "Steffen", family = "Prohaska"), person(given = c("Gregory", "S", "X", "E"), family = "Jefferis")), doi = "10.1016/j.neuron.2016.06.012", journal = "Neuron", month = "Jul", number = "2", pages = "293-311", title = "NBLAST: Rapid, Sensitive Comparison of Neuronal Structure and Construction of Neuron Family Databases"...

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

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 responses of my trained neural network are alwa...

...y gracias por leer mi mensaje: > Llevo utilizando unos meses R, vengo de SPSS, y estoy muy sorprendido con > su capacidad. > 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 to...

Hola a todos, y gracias por leer mi mensaje: Llevo utilizando unos meses R, vengo de SPSS, y estoy muy sorprendido con su capacidad. 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 h...

Dear List Members, I'm presently carrying out morphological analysis of a data set of neuronal structures. These are essentially 3D binary trees. In due course I will be trying to use discriminant analysis or other methods to classify these neurons based on morphological variables such as total tree length, segment number etc. I would like to calculate a 3D convex hull for a set of X,Y,...

Buenas, He estado leyendo publicaciones sobre las redes neuronales ( y el deep learning) pero no consigo entender el tipo de operaciones que se hacen en cada una de las capas de las redes neuronales. Necesito alguna explicacion más para tontos. ¿Alguien entiende bien lo que hace una red neuronal? Por ejemplo, un randomForest hace el ensamble por boostrap de á...

...rain) 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 network is to properly classify a number as positive or negative. Simple 1-layer network with a single neuron in each layer. Rcode: trainInput <- matrix(rnorm(10)) trainAnswers <- ifelse(trainInput <0, -1, 1) trainNeurons <- 1 trainingData <- mlptrain(inp=trainInput, neurons=trainNeurons, out=trainAnswers, it=1000) ## To call this network, we can see how it works on a set of known posit...

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 someone point me to an example where exclude and

...language mistakes in my sentences. I think, it is the good mail address to send my question, if not please tell me and forgive me. I am working on a project, and I use the nnet library. Our customers do not want us to install R on their machine, so we just use R for making the training of our neurons network. This part is good and we have the weights for each neurons and each links. The neuron network we used is a very simple one : 4 inputs for *one linear output* unit with just one hidden layer (with 5 neurons) between the inputs and the ouputs. So in R it is translated by the following...

...se help to understand this behavior. library('AMORE') ir <- rbind(iris3[,,1], iris3[,,2], iris3[,,3]) targets <- matrix(c(rep(c(1,0,0),50), rep(c(0,1,0),50), rep(c(0,0,1),50)), 150, 3, byrow=TRUE) samp <- c(sample(1:50,25), sample(51:100,25), sample(101:150,25)) net <- newff(n.neurons=c(4, 2, 3), # number of units per layer learning.rate.global=1e-2, # learning rate at which every neuron is trained momentum.global=5e-4, # momentum for every neuron error.criterium="LMS", # error criterium...

...rgive me, I have also sent this quetion to r-help, because the answer could be known from the programmers and the other R users :). I am working on a project, and I use the nnet library. Our customers do not want us to install R on their machine, so we just use R for making the training of our neurons network. This part is good and we have the weights for each neurons and each links. The neuron network we used is a very simple one : 4 inputs for *one linear output* unit with just one hidden layer (with 5 neurons) between the inputs and the ouputs. So in R it is translated by the following...

Estimados Les consulto por redes neuronales, hay diversos artículos como los siguientes (el último tienen un error actualmente). Pero mi pregunta va un poco por otro lado. http://www.r-bloggers.com/build-your-own-neural-network-classifier-in-r/ http://www.r-bloggers.com/classification-using-neural-net-in-r/ Básicamente se puede calcular...

A recent paper on visualisation (in Neuron, a leading neuroscience journal) surveyed how well previous articles in this journal labelled their graphs (e.g. axis labelling and describing their error bars). Of particular interest is that (only) 40% of plots labelled what their colorkey was showing (variable and units). The paper is at http:...

...ruben.marcuzzi en gmail.com> escribió: > Estimados > > > > Adjunto un archivo de texto separado por comas, muy simple como ejemplo, > luego el siguiente código explicaría el problema. Si ejecutan el código se > entenderá, creo. > > > > x <- read.csv("~/R/neuronal/x.csv", header=FALSE, sep=";") > > V1Binario <- model.matrix(~ factor(x$V1) - 1) > > # -1 no coloca como interceto, deja x$V1 sin nada, son los que no tienen > nada (nada, puerta, porton) > > V1Binario > > V2Binario <- model.matrix(~ factor(x$V2) -...

Hello everybody, I am afraid this might be a stupid question, but after scanning a little bit through the help archive and the internet, I didn't come up with an answer myself. I have done a principle component analysis on a data set, which yields the mean response of 14 olfactory neurons to 16 different odors. When plotting the result in a biplot, it nicely shows me the odors in different positions in the principle component space. Additionally, the neurons are shown as vectors within this plot. My question now is: what are the units of the axes? When doing the principle compo...

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.table('in.dat') colnames(All) <- paste('col',1:ncol(All),sep='') # Va...

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 save the model with a especific name, when i = 6, also I need to save the model with another name How i am doing, i am saving only the last model with n = 30 and with...