of Chlorophyll a can make the
> Eutrophication in lake along with other algeas.
> So I think they are dependent variables.
> Regards.
>
>
>
> ------------
> On Thu, 1/22/15, Charles Determan Jr wrote:
>
> Subject: Re: [R] Neural Network
) Is it possible to predict the Eutro. by these variables?
Many thanks for your help.
Regards,
On Thu, 1/22/15, Charles Determan Jr wrote:
Subject: Re: [R] Neural Network
roject.org>
Date: Thursday, January 22, 2015, 4:41 PM
Javad,
Fi
variables.
Regards.
On Thu, 1/22/15, Charles Determan Jr wrote:
Subject: Re: [R] Neural Network
roject.org>
Date: Thursday, January 22, 2015, 4:41 PM
Javad,
First,
please make sure to hit 'reply all' so that these
messages go
> 2) Is it possible to predict the Eutro. by these variables?
>
>
> Many thanks for your help.
> Regards,
>
>
>
>
>
>
>
> ----------------
> On Wed, 1/21/15, Charles Determan Jr wrote:
>
> Subject: Re: [R] Neural Network
> To
Javad,
You question is a little too broad to be answered definitively. Also, this
is not a code writing service. You should make a meaningful attempt and we
are here to help when you get stuck.
1. If you want to know if you can do neural nets, the answer is yes. The
three packages most commonl
2010/7/18 Arnaud Trébaol :
> Hi all,
>
> I am working for my master's thesis and I need to do a neural network to
> forecast stock market price, with also external inputs like technical
> indicators.
> I would like to know which function and package of R are more suitable for
> this study.
>
> Than
I'd start with the nnet library
type:
?nnet
CS
-
Corey Sparks, PhD
Assistant Professor
Department of Demography and Organization Studies
University of Texas at San Antonio
501 West Durango Blvd
Monterey Building 2.270C
San Antonio, TX 78207
210-458-3166
corey.sparks 'at' utsa.edu
https://row
From: "jude.r...@ubs.com"
Sent: Thursday, May 28, 2009 10:49:36 PM
Subject: Re: [R] Neural Network resource
The package AMORE appears to be more flexible, but I got very poor results
using it when I tried to improve the predictive accuracy of a
The package AMORE appears to be more flexible, but I got very poor
results using it when I tried to improve the predictive accuracy of a
regression model. I don't understand all the options well enough to be
able to fine tune it to get better predictions. However, using the
nnet() function in packa
assed the input dataset and tried to
> get the predictions, all the predicted values were identical! This confused
> me a bit and was wondering whether my understanding of the Neural Network was
> wrong.
>
> Have you ever faced anything like it?
>
> Regards,
> Indrajit
>
&
###
Here I am trying to predict Oxygen levels using the 6 independent
variables. But whenever I am trying to run a prediction - I am getting constant
values throughout (In the above example - the values of pred).
Thanks & Regards,
Indrajit
- Original Message
F
> I fed this data into a Neural network (3 hidden layers with 6 neurons in each
> layer) and trained the network. When I passed the input dataset and tried to
> get the predictions, all the predicted values were identical! This confused
> me a bit and was wondering whether my understanding of th
understanding of the Neural Network was
wrong.
Have you ever faced anything like it?
Regards,
Indrajit
From: "markle...@verizon.net"
Sent: Wednesday, May 27, 2009 7:54:59 PM
Subject: Re: [R] Neural Network resource
Hi: I've never used that p
There's a link on the CRAN page for the AMORE package which apears to
have some cool information:
http://wiki.r-project.org/rwiki/doku.php?id=packages:cran:amore
Seems like an interesting package, I hadn't actually heard of it
before your post.
HTH,
Tony
On 27 May, 09:13, Indrajit Sengupta wro
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