Displaying 20 results from an estimated 5000 matches similar to: "? predict.nnet"
2009 Nov 20
0
problem with predict from nnet package
Hi,
I’m having mayor issues with predict from the nnet package.
I’m training a neural network for forecasting. I trained the network with
info from 1995 to 2009 and I want to forecast month by month 2010.(the
network forecasts one month at a time).
Since I have to do iterative forecasting, im using predict several times
including, including the new forecast each time, but for some reason
2005 Jul 22
2
about nnet package
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
2000 Jul 22
1
maketitle garbles the title in package nnet (PR#613)
The TITLE for the nnet package is garbled: it comes out as
nnet Feed-forward neural networks and multinomial log-linear
nnet Feed-forward neural networks and multinomial log-linear models
The problem is in maketitle:
auk% cat DESCRIPTION
Bundle: VR
Version: 6.1-9
Date: 2000/07/11
Depends: R (>= 1.1)
Author: S original by Venables & Ripley.
R port by Brian Ripley
2000 Oct 24
1
Predict.nnet ?
Hi,
I have a problem with predict.nnet when I try to use it. It crashes R with a
memory access violation.
platform Windows
arch x86
os Win32
system x86, Win32
status
major 1
minor 1.1
year 2000
month August
day 15
language R
I admit the data set is quite large ~ [3000, 101] and its a 3 class problem.
I know that it works fine when there is a single target. I wonder
2009 Nov 02
1
modifying predict.nnet() to function with errorest()
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
2010 Dec 10
2
Need help on nnet
Hi,
Am working on neural network.
Below is the coding and the output
> library (nnet)
> uplift.nn<-nnet (PVU~ConsumerValue+Duration+PromoVolShare,y,size=3)
# weights: 16
initial value 4068.052704
final value 3434.194253
converged
> summary (uplift.nn)
a 3-3-1 network with 16 weights
options were -
b->h1 i1->h1 i2->h1 i3->h1
16.64 6.62 149.93
2012 Sep 21
0
using neural network in R (nnet)
Hi all,
I have considered neural network to classify the health status of the cow.
I found a very neatly written R codes for classification method in
here<http://home.strw.leidenuniv.nl/~jarle/IAC/RRoutines/classification-example.R>
.
It would be very helpful if you can answer some of the questions, that I am
struggling with,
I have set of time series data from different animals, I use
2004 Oct 18
1
nnet learning
Hi,
I am trying to make a neural network learning a "noisy sine wave".
Suppose I generate my data like so..
x <- seq(-2*pi, 2*pi, length=500)
y <- sin(x) + rnorm(500, sd=sqrt(0.075))
I then train the neural net on the first 400 points using
c <- nnet(as.matrix(x[1:400]),as.matrix(y[1:400]), size=3, maxit=10000,
abstol=0.075, decay=0.007)
Inspecting the fit of the training
2006 Nov 22
1
What training algorithm does nnet package use?
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? I'm
2011 Jan 05
0
Nnet and AIC: selection of a parsimonious parameterisation
Hi All,
I am trying to use a neural network for my work, but I am not sure about my
approach to select a parsimonious model. In R with nnet, the IAC has
not been defined for a feed-forward neural network with a single hidden layer.
Is this because it does not make sens mathematically in this case?
For example, is this pseudo code sensible?
Thanks in advance for your help. I am sorry if this
2004 Nov 29
0
R: nnet questions
hi all
i'm new to the area of neural networks. i've been reading some
references and seem to understand some of the learning algorithms. i am
very familiar with regression and would just like to see how neural nets
handle this problem so i've been using the nnet package.
i simply want to use a 3 layer neural net, ie 1 input, 1 hidden layer
(where the hidden layer is linear, since i
2007 Jan 28
2
nnet question
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
2011 Nov 27
0
nnet plot
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)
2011 Nov 28
0
Plot nnet
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)
2009 Feb 18
1
Training nnet in two ways, trying to understand the performance difference - with (i hope!) commented, minimal, self-contained, reproducible code
Dear all,
Objective: I am trying to learn about neural networks. I want to see
if i can train an artificial neural network model to discriminate
between spam and nonspam emails.
Problem: I created my own model (example 1 below) and got an error of
about 7.7%. I created the same model using the Rattle package (example
2 below, based on rattles log script) and got a much better error of
about
2010 Jan 29
0
Help interpreting libarary(nnet) script output..URGENT
Hello,
I am pretty new to R. I am working on neural network classifiers and I am
feeding the nnet input from different regions of interest (fMRI data). The
script that I am using is this:
library (MASS)
heap_lda <-
data.frame(as.matrix(t(read.table(file="R_10_5runs_matrix9.txt")))*100000,syll
= c(rep("heap",3),rep("hoop",3),rep("hop",3)))
library(nnet)
2010 Jun 02
1
nnet: cannot coerce class c("terms", "formula") into a data.frame
Dearest all,
Objective: I am now learning neural networks. I want to see how well can
train an artificial neural network model to discriminate between the two
files I am attaching with this message.
http://r.789695.n4.nabble.com/file/n2240582/3dMaskDump.txt 3dMaskDump.txt
http://r.789695.n4.nabble.com/file/n2240582/test_vowels.txt test_vowels.txt
Question: when I am attempting to run
2011 May 11
0
Init nnetTs (or nnet?) with a former Neural Net
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.:
2010 Jun 17
0
help with neural network nnet package
HI, Dear R community,
I am using the nnet to fit a neural network model to do classification on
binary target variable (0, 1). I am using the following codes:
nnet.fit<-nnet(as.factor(out) ~ ., data=train, size=5, rang=0.3,
decay=5e-4, maxit=500)
I want to know what is the activation function for the original inputs, is
it sigmoid activation function?
and what is the output activation
2003 Aug 19
3
On the Use of the nnet Library
Dear List,
I am trying to solve a problem by the neural network method(library:
nnet). The problem is to express Weight in terms of Age , Sex and Height
for twenty people. The data frame consists of 20 observations with four
variables: Sex, Age, Height and Weight. Sex is treated as a factor, Age
and Weight are variables normalized to unity, as usual. I wanted to
construct a neural network, and so