[R] Neural Network
Charles Determan Jr
deter088 at umn.edu
Mon Jan 26 16:13:13 CET 2015
Javad,
You misunderstand what is meant be 'dependent' and 'independent'
variables. What you are describing is with respect to statistical
independence. Please review these basic statistical concepts
http://en.wikipedia.org/wiki/Dependent_and_independent_variables. Perhaps,
the terms 'explanatory' (e.g. your phosphorus, nitrogen, etc.) and
'response' (e.g. eutrophication) variables are more approachable.
Now, as I was saying in my first response, you don't appear to have a
dependent/response variable (i.e. Eutrophication). No where in your data
do you say that Eutrophication was measured or is represented in any way.
Now, I assume you have 'a priori' knowledge that those variables are
involved with eutrophication. You are now asking if you can predict
eutrophication from these variables. Well, without something for a
statistical model to evaluate against there is no means to do so, hence the
exploratory, unsupervised analysis I recommended.
With respect to your other question, "How can I predict these variables by
NN?", well you need something to test against. For example, let's say I
want to predict how much ice cream will be sold today and I have a bunch of
data with amounts of ice cream sold but no other data. No matter how you
approach this problem, you cannot get much out of a list of numbers with
nothing to test against.
Now, if my ice cream data has the amounts of ice cream and temperatures of
each day associated with the respective sold amount, now I can do
something. I can do my basic linear regression so help predict how much
ice cream will be sold given today's temperature.
The same appears to be true of your data. You have your variables, you
have all of your response variables (assuming you are trying to predict
Nitrogen, Chlorophyll, etc.) but nothing to test against. The best you may
have is your time data which I can only assume is actual dates? If so, you
could do some form of prediction based on the date. If your data is just
every two weeks (no date, just repeated measures) you could analyze it
temporally to see if the various nutrients are changing over time and
potentially extrapolate (with caution) where the levels may ultimately
reach. This may be of interest to you.
As a last point, seeing as this is environmental analysis you could also
try the R-sig-ecology mailing list. I am admittedly not an ecologist and
there may be some other approaches or methods that could possibly be used.
Feel free to sign up on that list here
https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
I hope this explanation helps you get a better grasp of what you are trying
to accomplish.
Regards,
On Sat, Jan 24, 2015 at 12:41 AM, javad bayat <jbayat67 at yahoo.com> wrote:
> Dear Charles;
> I think my variables are dependent. For e.g. the concentration of
> Phosphorus, Nitrogen, Silica and etc. have effect on the present of
> Chlorophyll a and the concentration 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 <deter088 at umn.edu> wrote:
>
> Subject: Re: [R] Neural Network
> To: "javad bayat" <jbayat67 at yahoo.com>, "r-help at r-project.org" <
> r-help at r-project.org>
> Date: Thursday, January 22, 2015, 4:41 PM
>
> Javad,
> First,
> please make sure to hit 'reply all' so that these
> messages go to the R help list so others (many far more
> skilled than I) may possibly chime in.
> The problem here is that you appear
> to have no dependent variable (i.e. no eutrophication
> variable). Without it, there is no way to a typical
> 'supervised' analysis. Given that this is likely a
> regression type problem (I assume eutrophication would be
> continous) I'm not quite sure 'supervised' is
> the correct description but it furthers my point that you
> need a dependent variable for any neuralnet algorithm I am
> aware of. As such, if you don't have a dependent
> variable then you will need to look at unsupervised methods
> such as PCA. Other users may have other
> suggestions.
> Regards,Charles
> On Wed, Jan 21, 2015 at
> 11:36 PM, javad bayat <jbayat67 at yahoo.com>
> wrote:
> Dear
> Charles;
>
> Many thanks for your attention. what I want to know is: How
> can I predict the Eutrophication by these parameters in the
> future?
>
> These variables are the most important variables that
> control the Eutro. in lakes.
>
> Let me break it to two parts.
>
> 1) How can I predict these variables by NN?
>
> 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 <deter088 at umn.edu>
> wrote:
>
>
>
> Subject: Re: [R] Neural Network
>
> To: "javad bayat" <jbayat67 at yahoo.com>
>
> Cc: "r-help at r-project.org"
> <r-help at r-project.org>
>
> Date: Wednesday, January 21, 2015, 9:10 PM
>
>
>
> 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 commonly used (that I
> know
>
> of) are 'neuralnet', 'nnet' and
>
> 'RSNNS'. You should look in to these package
>
> documentation for how to use them. There are also
> many
>
> examples online if you simply google them.
>
> 2. You question is unclear, are you
>
> wanting to predict all the variables (e.g. phosphorus,
> Total
>
> N, etc.) or do you have some metric for
> eutrophication?
>
> What exactly is the model supposed to predict?
>
> 3. If you want to know if a
>
> neuralnet is appropriate, that is more of a statistical
>
> question. It depends more on the question you want to
>
> answer. Given your temporal data, you may want to look
> in
>
> to mixed effects models (e.g nlme, lme4) as another
>
> potential approach.
>
> Regards,
>
> On Tue, Jan 20, 2015 at
>
> 11:35 PM, javad bayat via R-help <r-help at r-project.org>
>
> wrote:
>
> Dear
>
> all;
>
>
>
> I am the new user of R. I want to simulation or
> prediction
>
> the Eutrophication of a lake. I have weekly data(almost
> for
>
> two years) for Total phosphorus, Total N, pH, Chlorophyll
> a,
>
> Alkalinity, Silica.
>
>
>
> Can I predict the Eutrophication by Neural Network in
> R?
>
>
>
> How can I simulation the Eutrophication by these
>
> parameter?
>
>
>
> please help me to write the codes.
>
>
>
> many thanks.
>
>
>
>
>
>
>
> ______________________________________________
>
>
>
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>
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>
>
>
> and provide commented, minimal, self-contained,
> reproducible
>
> code.
>
>
>
>
>
>
>
>
>
> --
>
> Dr. Charles Determan, PhD
>
> Integrated Biosciences
>
>
>
>
>
>
>
>
> --
> Dr. Charles Determan, PhD
> Integrated Biosciences
>
>
>
--
Dr. Charles Determan, PhD
Integrated Biosciences
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