Thread Subject: newrbe

Hi, I am working on radial basis network to predict protein conc. Part of the task is to compare result between newrb & newrbe. I have no problem with the newrb but for newrbe I got this warning:

Warning: Rank deficient, rank = 5, tol = 2.7195e-014.
 > In newrbe>designrbe at 122
     In newrbe at 105
     In RBFnormBnewrbe01_VCC_TRAINOPTIMIZE at 64

1.below are my source (newrbe):

K=TRAINOPTIMIZE;
[r,c]=size(K);

GOAL=0.5;%SPREAD=input
SPREAD=20;
MN=24; % sample points
DF=1;
%net.layers{1}.transferFcn='radbas';
%net.layers{2}.transferFcn='purelin';

net=newrbe(P,T,SPREAD);
Y=sim(net,P);


2.below are my source (newrb):

GOAL=0.5; %SPREAD=input
SPREAD=20;
MN=24; % sample points
DF=1;
%net.layers{1}.transferFcn='radbas';
%net.layers{2}.transferFcn='purelin';

net=newrb(P,T,GOAL,SPREAD);
Y=sim(net,P);

note: i got the result as follow:
NEWRB, neurons = 0, MSE = 0.130203


where i could be wrong?or did i miss something important?

On Nov 15, 9:15 pm, "aurikel Radzali" <suriar...@gmail.com> wrote:
> Hi, I am working on radial basis network to predict protein conc. Part of the task is to compare result between newrb & newrbe. I have no problem with the newrb but for newrbe I got this warning:
>
> Warning: Rank deficient, rank = 5,  tol =   2.7195e-014.
>  >  In newrbe>designrbe at 122
>      In newrbe at 105
>      In RBFnormBnewrbe01_VCC_TRAINOPTIMIZE at 64
>
> 1.below are my source (newrbe):
>
> K=TRAINOPTIMIZE;
> [r,c]=size(K);
>
> GOAL=0.5;%SPREAD=input
> SPREAD=20;
> MN=24; % sample points
> DF=1;
> %net.layers{1}.transferFcn='radbas';
> %net.layers{2}.transferFcn='purelin';
>
> net=newrbe(P,T,SPREAD);
> Y=sim(net,P);
>
> 2.below are my source (newrb):
>
> GOAL=0.5; %SPREAD=input
> SPREAD=20;
> MN=24; % sample points
> DF=1;
> %net.layers{1}.transferFcn='radbas';
> %net.layers{2}.transferFcn='purelin';
>
> net=newrb(P,T,GOAL,SPREAD);
> Y=sim(net,P);
>
> note: i got the result as follow:
> NEWRB, neurons = 0, MSE = 0.130203
>
> where i could be wrong?or did i miss something important?

You say "I have no problem with the newrb".
However, you report "neurons = 0, MSE = 0.130203"

which makes no sense to me. Furthermore, the value 0.13
means nothing unless it is compared to a reference.
What is mean(var(T))?

Greg

Greg Heath <heath@alumni.brown.edu> wrote in message <dc9ef436-338f-40fb-aa39-d679e47f6b1d@j11g2000vbi.googlegroups.com>...
> On Nov 15, 9:15?pm, "aurikel Radzali" <suriar...@gmail.com> wrote:
> > Hi, I am working on radial basis network to predict protein conc. Part of the task is to compare result between newrb & newrbe. I have no problem with the newrb but for newrbe I got this warning:
> >
> > Warning: Rank deficient, rank = 5, ?tol = ? 2.7195e-014.
> > ?> ?In newrbe>designrbe at 122
> > ? ? ?In newrbe at 105
> > ? ? ?In RBFnormBnewrbe01_VCC_TRAINOPTIMIZE at 64
> >
> > 1.below are my source (newrbe):
> >
> > K=TRAINOPTIMIZE;
> > [r,c]=size(K);
> >
> > GOAL=0.5;%SPREAD=input
> > SPREAD=20;
> > MN=24; % sample points
> > DF=1;
> > %net.layers{1}.transferFcn='radbas';
> > %net.layers{2}.transferFcn='purelin';
> >
> > net=newrbe(P,T,SPREAD);
> > Y=sim(net,P);
> >
> > 2.below are my source (newrb):
> >
> > GOAL=0.5; %SPREAD=input
> > SPREAD=20;
> > MN=24; % sample points
> > DF=1;
> > %net.layers{1}.transferFcn='radbas';
> > %net.layers{2}.transferFcn='purelin';
> >
> > net=newrb(P,T,GOAL,SPREAD);
> > Y=sim(net,P);
> >
> > note: i got the result as follow:
> > NEWRB, neurons = 0, MSE = 0.130203
> >
> > where i could be wrong?or did i miss something important?
>
> You say "I have no problem with the newrb".
> However, you report "neurons = 0, MSE = 0.130203"
>
> which makes no sense to me. Furthermore, the value 0.13
> means nothing unless it is compared to a reference.
> What is mean(var(T))?
>
> Greg

Hi, actually i have a problem with newrb too except it does not produce warning like the newrbe.

--> this is the newrb code:

GOAL=0.5;
SPREAD=5;
MN=24; % sample points
DF=1;

%net.layers{1}.transferFcn='radbas';
%net.layers{2}.transferFcn='purelin';

net=newrb(P,T,GOAL,SPREAD);

Y=sim(net,P);
e=T-Y;
msetrain=mse(e)

--> this is the result:
NEWRB, neurons = 0, MSE = 0.130203

msetrain =

    0.0018

why the mse value is different? the mean(var(T)) is 0.1359

On Nov 16, 4:23 am, "aurikel Radzali" <suriar...@gmail.com> wrote:
> GregHeath<he...@alumni.brown.edu> wrote in message <dc9ef436-338f-40fb-aa39-d679e47f6...@j11g2000vbi.googlegroups.com>...
> > On Nov 15, 9:15?pm, "aurikel Radzali" <suriar...@gmail.com> wrote:
> > > Hi, I am working on radial basis network to predict protein conc. Part of the task is to compare result between newrb & newrbe. I have no problem with the newrb but for newrbe I got this warning:
>
> > > Warning: Rank deficient, rank = 5, ?tol = ? 2.7195e-014.
> > > ?> ?In newrbe>designrbe at 122
> > > ? ? ?In newrbe at 105
> > > ? ? ?In RBFnormBnewrbe01_VCC_TRAINOPTIMIZE at 64
>
> > > 1.below are my source (newrbe):
>
> > > K=TRAINOPTIMIZE;
> > > [r,c]=size(K);
>
> > > GOAL=0.5;%SPREAD=input
> > > SPREAD=20;
> > > MN=24; % sample points
> > > DF=1;
> > > %net.layers{1}.transferFcn='radbas';
> > > %net.layers{2}.transferFcn='purelin';
>
> > > net=newrbe(P,T,SPREAD);
> > > Y=sim(net,P);
>
> > > 2.below are my source (newrb):
>
> > > GOAL=0.5; %SPREAD=input
> > > SPREAD=20;
> > > MN=24; % sample points
> > > DF=1;
> > > %net.layers{1}.transferFcn='radbas';
> > > %net.layers{2}.transferFcn='purelin';
>
> > > net=newrb(P,T,GOAL,SPREAD);
> > > Y=sim(net,P);
>
> > > note: i got the result as follow:
> > > NEWRB, neurons = 0, MSE = 0.130203
>
> > > where i could be wrong?or did i miss something important?
>
> > You say "I have no problem with the newrb".
> > However, you report "neurons = 0, MSE = 0.130203"
>
> > which makes no sense to me. Furthermore, the value 0.13
> > means nothing unless it is compared to a reference.
> > What is mean(var(T))?
>
> >Greg
>
> Hi, actually i have a problem with newrb too except
> it does not produce warning like the newrbe.
>
> --> this is the newrb code:

size(P) = ?
minmax(P) = ?
size(T) = ?
minmax(T) = ?

> GOAL=0.5;

Note: In my version 6.5 this is SSEgoal, NOT MSEgoal;

Why did you choose this value?

For the best constant model y = mean of targets:

y00 = repmat(mean(T,2),1,size(T,2));
e00 = T-y00;
SSE00 = sse(e00)

For newrb, it is desirable to have

SSEgoal < SSE00/100

so that

R^2 = 1-SSE/SSE00 > 0.99


> SPREAD=5;

Why did you choose this value?

How does it compare to

0.5*mean(median(dist(P,P')))?


> MN=24; % sample points
> DF=1;
>
> %net.layers{1}.transferFcn='radbas';
> %net.layers{2}.transferFcn='purelin';
>
> net=newrb(P,T,GOAL,SPREAD);

[net, tr] = newrb(P,T,GOAL,SPREAD);

> Y=sim(net,P);
> e=T-Y;
> msetrain=mse(e)

compare with tr.perf(end)

> --> this is the result:
> NEWRB, neurons = 0, MSE = 0.130203

If N ~ 24, This is not inconsistent with
mean(var(T)) = 0.1359.

Where is the tabulation for neurons > 0?

> msetrain =
>
> 0.0018

For how many neurons?


> why the mse value is different?

Different number of neurons
What is tr.epoch(end)?

>the mean(var(T)) is 0.1359

MSE(neurons = 0) = (N-1)*mean(var(T'))/N

Hope this helps.

Greg

Greg Heath <heath@alumni.brown.edu> wrote in message <9bfd2ece-92b5-432f-a82c-61238af4d20c@j4g2000yqe.googlegroups.com>...
> On Nov 16, 4:23 am, "aurikel Radzali" <suriar...@gmail.com> wrote:
> > GregHeath<he...@alumni.brown.edu> wrote in message <dc9ef436-338f-40fb-aa39-d679e47f6...@j11g2000vbi.googlegroups.com>...
> > > On Nov 15, 9:15?pm, "aurikel Radzali" <suriar...@gmail.com> wrote:
> > > > Hi, I am working on radial basis network to predict protein conc. Part of the task is to compare result between newrb & newrbe. I have no problem with the newrb but for newrbe I got this warning:
> >
> > > > Warning: Rank deficient, rank = 5, ?tol = ? 2.7195e-014.
> > > > ?> ?In newrbe>designrbe at 122
> > > > ? ? ?In newrbe at 105
> > > > ? ? ?In RBFnormBnewrbe01_VCC_TRAINOPTIMIZE at 64
> >
> > > > 1.below are my source (newrbe):
> >
> > > > K=TRAINOPTIMIZE;
> > > > [r,c]=size(K);
> >
> > > > GOAL=0.5;%SPREAD=input
> > > > SPREAD=20;
> > > > MN=24; % sample points
> > > > DF=1;
> > > > %net.layers{1}.transferFcn='radbas';
> > > > %net.layers{2}.transferFcn='purelin';
> >
> > > > net=newrbe(P,T,SPREAD);
> > > > Y=sim(net,P);
> >
> > > > 2.below are my source (newrb):
> >
> > > > GOAL=0.5; %SPREAD=input
> > > > SPREAD=20;
> > > > MN=24; % sample points
> > > > DF=1;
> > > > %net.layers{1}.transferFcn='radbas';
> > > > %net.layers{2}.transferFcn='purelin';
> >
> > > > net=newrb(P,T,GOAL,SPREAD);
> > > > Y=sim(net,P);
> >
> > > > note: i got the result as follow:
> > > > NEWRB, neurons = 0, MSE = 0.130203
> >
> > > > where i could be wrong?or did i miss something important?
> >
> > > You say "I have no problem with the newrb".
> > > However, you report "neurons = 0, MSE = 0.130203"
> >
> > > which makes no sense to me. Furthermore, the value 0.13
> > > means nothing unless it is compared to a reference.
> > > What is mean(var(T))?
> >
> > >Greg
> >
> > Hi, actually i have a problem with newrb too except
> > it does not produce warning like the newrbe.
> >
> > --> this is the newrb code:
>
> size(P) = ?
> minmax(P) = ?
> size(T) = ?
> minmax(T) = ?
>
> > GOAL=0.5;
>
> Note: In my version 6.5 this is SSEgoal, NOT MSEgoal;
> -----------> I just put random value, I do not know what value should i choose.

> Why did you choose this value?
>
> For the best constant model y = mean of targets:
>
> y00 = repmat(mean(T,2),1,size(T,2));
> e00 = T-y00;
> SSE00 = sse(e00)
>
> For newrb, it is desirable to have
>
> SSEgoal < SSE00/100
>
> so that
>
> R^2 = 1-SSE/SSE00 > 0.99
> -----------> i do not understand, what is the purpose of this?
>
> > SPREAD=5;
>
> Why did you choose this value?
> ------------------> i just put some value, i don't know what values should i use? (i thought the best spread is obtained through trial and error method)

> How does it compare to
>
> 0.5*mean(median(dist(P,P')))?
> ---------> do you mean compare this and spread=5?
------------->btw, 0.5*mean(median(dist(P,P')))=1.0815
>
> > MN=24; % sample points
> > DF=1;
> >
> > %net.layers{1}.transferFcn='radbas';
> > %net.layers{2}.transferFcn='purelin';
> >
> > net=newrb(P,T,GOAL,SPREAD);
>
> [net, tr] = newrb(P,T,GOAL,SPREAD);
>
-----------------> what is the different between the those two? What is the purpose of putting [net,tr]?

> > Y=sim(net,P);
> > e=T-Y;
> > msetrain=mse(e)
>
> compare with tr.perf(end)
> --------------tr.perf(end)=0.0018


> > --> this is the result:
> > NEWRB, neurons = 0, MSE = 0.130203
>
> If N ~ 24, This is not inconsistent with
> mean(var(T)) = 0.1359.
> ___________> I'm really sorry, but i truly do not understand what do you by If N ~ 24, This is not inconsistent with mean(var(T)) = 0.1359
----------------------->how it suppose to be??

> Where is the tabulation for neurons > 0?
>
> > msetrain =
> >
> > 0.0018
>
> For how many neurons?
> -------------->Number of nodes in hidden layer=2.0000e+000
>
> > why the mse value is different?
>
> Different number of neurons
> What is tr.epoch(end)?
> ---------> 2

> >the mean(var(T)) is 0.1359
>
> MSE(neurons = 0) = (N-1)*mean(var(T'))/N
> -------------> owhh..thats why i get the MSE=0.1302

> Hope this helps.
>
> Greg

==============> Thanks, I still have some questions.

based on your advice, %For newrb, it is desirable to have SSEgoal < SSE00/100
SSE00=3.1249
SSEm=SSE00/100 %produce 0.0312

so i choose my goal 0.0005 % since SSEgoal < SSE00/100. is this right?

On Nov 19, 1:36 am, "aurikel Radzali" <suriar...@gmail.com> wrote:
> Greg Heath <he...@alumni.brown.edu> wrote in message <9bfd2ece-92b5-432f-a82c-61238af4d...@j4g2000yqe.googlegroups.com>...
> > On Nov 16, 4:23 am, "aurikel Radzali" <suriar...@gmail.com> wrote:
> > > GregHeath<he...@alumni.brown.edu> wrote in message <dc9ef436-338f-40fb-aa39-d679e47f6...@j11g2000vbi.googlegroups.com>...
> > > > On Nov 15, 9:15?pm, "aurikel Radzali" <suriar...@gmail.com> wrote:
> > > > > Hi, I am working on radial basis network to predict protein conc.
Part of the task is to compare result between newrb & newrbe. I have
no
problem with the newrb but for newrbe I got this warning:
>
> > > > > Warning: Rank deficient, rank = 5, ?tol = ? 2.7195e-014.
> > > > > ?> ?In newrbe>designrbe at 122
> > > > > ? ? ?In newrbe at 105
> > > > > ? ? ?In RBFnormBnewrbe01_VCC_TRAINOPTIMIZE at 64
>
> > > > > 1.below are my source (newrbe):
>
> > > > > K=TRAINOPTIMIZE;
> > > > > [r,c]=size(K);
>
> > > > > GOAL=0.5;%SPREAD=input
> > > > > SPREAD=20;
> > > > > MN=24; % sample points
> > > > > DF=1;
> > > > > %net.layers{1}.transferFcn='radbas';
> > > > > %net.layers{2}.transferFcn='purelin';
>
> > > > > net=newrbe(P,T,SPREAD);
> > > > > Y=sim(net,P);
>
> > > > > 2.below are my source (newrb):
>
> > > > > GOAL=0.5; %SPREAD=input
> > > > > SPREAD=20;
> > > > > MN=24; % sample points
> > > > > DF=1;
> > > > > %net.layers{1}.transferFcn='radbas';
> > > > > %net.layers{2}.transferFcn='purelin';
>
> > > > > net=newrb(P,T,GOAL,SPREAD);
> > > > > Y=sim(net,P);
>
> > > > > note: i got the result as follow:
> > > > > NEWRB, neurons = 0, MSE = 0.130203
>
> > > > > where i could be wrong?or did i miss something important?
>
> > > > You say "I have no problem with the newrb".
> > > > However, you report "neurons = 0, MSE = 0.130203"
>
> > > > which makes no sense to me. Furthermore, the value 0.13
> > > > means nothing unless it is compared to a reference.
> > > > What is mean(var(T))?
>
> > > >Greg
>
> > > Hi, actually i have a problem with newrb too except
> > > it does not produce warning like the newrbe.
>
> > > --> this is the newrb code:
>
> > size(P) = ?
> > minmax(P) = ?
> > size(T) = ?
> > minmax(T) = ?


Please answer the questions.


> > > GOAL=0.5;
>
> > Note: In my version 6.5 this is SSEgoal, NOT MSEgoal;

> -----------> I just put random value, I do not know what
> value should i choose.

> > Why did you choose this value?
>
> > For the best constant model y = mean of targets:
>
> > y00 = repmat(mean(T,2),1,size(T,2));
> > e00 = T-y00;
> > SSE00 = sse(e00)
>
> > For newrb, it is desirable to have
>
> > SSEgoal < SSE00/100
>
> > so that
>
> > R^2 = 1-SSE/SSE00 > 0.99

> -----------> i do not understand, what is the purpose of this?

R^2 (coefficient of determination) is a measure of the
fraction of output variance that is represented by the model.
See any statistic book that covers regression.

http://en.wikipedia.org/wiki/Coefficient_of_determination

> > > SPREAD=5;
>
> > Why did you choose this value?

> ------------------> i just put some value, i don't know what
values should i use? (i thought the best spread is obtained
> through trial and error method)

True, but why whistle in the dark when you can quickly estimate
a few charcteristic distances to help limit the search?

> > How does it compare to
>
> > 0.5*mean(median(dist(P,P')))?

Typical half-distance between data points. More useful
when the data points are either cluster centers from a previous
cluster analysis or data points selected as neurons.

> ---------> do you mean compare this and spread=5?

Yes.

> ------------->btw, 0.5*mean(median(dist(P,P')))=1.0815

What is it for hidden neurons ?

> > > MN=24; % sample points
> > > DF=1;
>
> > > %net.layers{1}.transferFcn='radbas';
> > > %net.layers{2}.transferFcn='purelin';
>
> > > net=newrb(P,T,GOAL,SPREAD);
>
> > [net, tr] = newrb(P,T,GOAL,SPREAD);
>
> -----------------> what is the different between the those two?
>What is the purpose of putting [net,tr]?

tr is the training record

help newrb
doc newrb

> > > Y=sim(net,P);
> > > e=T-Y;
> > > msetrain=mse(e)
>
> > compare with tr.perf(end)

> --------------tr.perf(end)=0.0018

> > > --> this is the result:
> > > NEWRB, neurons = 0, MSE = 0.130203
>
> > If N ~ 24, This is not inconsistent with
> > mean(var(T)) = 0.1359.

> ___________> I'm really sorry, but i truly do not
understand what do you by If N ~ 24,
This is not inconsistent with mean(var(T)) = 0.1359
>
> ----------------------->how it suppose to be??

If neurons = 0. Then the the output is a constant
equal to the bias. To minimize SSE, the constant must
be mean(T). The resulting MSE is (N-1)*var(T)/N

> > Where is the tabulation for neurons > 0?
>
> > > msetrain =
>
> > > 0.0018
>
> > For how many neurons?
> > -------------->Number of nodes in hidden layer=2.0000e+000
>
> > > why the mse value is different?
>
> > Different number of neurons
> > What is tr.epoch(end)?
> > ---------> 2
> > >the mean(var(T)) is 0.1359
>
> > MSE(neurons = 0) = (N-1)*mean(var(T'))/N
> > -------------> owhh..thats why i get the MSE=0.1302
> > Hope this helps.
>
> > Greg
>
> ==============> Thanks, I still have some questions.
>
> based on your advice, %For newrb, it is desirable to have SSEgoal < SSE00/100
> SSE00=3.1249
> SSEm=SSE00/100 %produce 0.0312
>
> so i choose my goal 0.0005 % since SSEgoal < SSE00/100. is this right?

I would use 0.02.

Hope this helps.

Greg

Greg Heath <heath@alumni.brown.edu> wrote in message <f88c4240-7211-4544-9ca1-f5a6568454cf@f20g2000vbl.googlegroups.com>...
> On Nov 19, 1:36 am, "aurikel Radzali" <suriar...@gmail.com> wrote:
> > Greg Heath <he...@alumni.brown.edu> wrote in message <9bfd2ece-92b5-432f-a82c-61238af4d...@j4g2000yqe.googlegroups.com>...
> > > On Nov 16, 4:23 am, "aurikel Radzali" <suriar...@gmail.com> wrote:
> > > > GregHeath<he...@alumni.brown.edu> wrote in message <dc9ef436-338f-40fb-aa39-d679e47f6...@j11g2000vbi.googlegroups.com>...
> > > > > On Nov 15, 9:15?pm, "aurikel Radzali" <suriar...@gmail.com> wrote:
> > > > > > Hi, I am working on radial basis network to predict protein conc.
> Part of the task is to compare result between newrb & newrbe. I have
> no
> problem with the newrb but for newrbe I got this warning:
> >
> > > > > > Warning: Rank deficient, rank = 5, ?tol = ? 2.7195e-014.
> > > > > > ?> ?In newrbe>designrbe at 122
> > > > > > ? ? ?In newrbe at 105
> > > > > > ? ? ?In RBFnormBnewrbe01_VCC_TRAINOPTIMIZE at 64
> >
> > > > > > 1.below are my source (newrbe):
> >
> > > > > > K=TRAINOPTIMIZE;
> > > > > > [r,c]=size(K);
> >
> > > > > > GOAL=0.5;%SPREAD=input
> > > > > > SPREAD=20;
> > > > > > MN=24; % sample points
> > > > > > DF=1;
> > > > > > %net.layers{1}.transferFcn='radbas';
> > > > > > %net.layers{2}.transferFcn='purelin';
> >
> > > > > > net=newrbe(P,T,SPREAD);
> > > > > > Y=sim(net,P);
> >
> > > > > > 2.below are my source (newrb):
> >
> > > > > > GOAL=0.5; %SPREAD=input
> > > > > > SPREAD=20;
> > > > > > MN=24; % sample points
> > > > > > DF=1;
> > > > > > %net.layers{1}.transferFcn='radbas';
> > > > > > %net.layers{2}.transferFcn='purelin';
> >
> > > > > > net=newrb(P,T,GOAL,SPREAD);
> > > > > > Y=sim(net,P);
> >
> > > > > > note: i got the result as follow:
> > > > > > NEWRB, neurons = 0, MSE = 0.130203
> >
> > > > > > where i could be wrong?or did i miss something important?
> >
> > > > > You say "I have no problem with the newrb".
> > > > > However, you report "neurons = 0, MSE = 0.130203"
> >
> > > > > which makes no sense to me. Furthermore, the value 0.13
> > > > > means nothing unless it is compared to a reference.
> > > > > What is mean(var(T))?
> >
> > > > >Greg
> >
> > > > Hi, actually i have a problem with newrb too except
> > > > it does not produce warning like the newrbe.
> >
> > > > --> this is the newrb code:
> >
> > > size(P) = ?
> > > minmax(P) = ?
> > > size(T) = ?
> > > minmax(T) = ?
>
>
> Please answer the questions.
---->size(P) =3 24
       size(T) =1 24

>
> > > > GOAL=0.5;
> >
> > > Note: In my version 6.5 this is SSEgoal, NOT MSEgoal;
>
> > -----------> I just put random value, I do not know what
> > value should i choose.
>
> > > Why did you choose this value?
> >
> > > For the best constant model y = mean of targets:
> >
> > > y00 = repmat(mean(T,2),1,size(T,2));
> > > e00 = T-y00;
> > > SSE00 = sse(e00)
> >
> > > For newrb, it is desirable to have
> >
> > > SSEgoal < SSE00/100
> >
> > > so that
> >
> > > R^2 = 1-SSE/SSE00 > 0.99
>
> > -----------> i do not understand, what is the purpose of this?
>
> R^2 (coefficient of determination) is a measure of the
> fraction of output variance that is represented by the model.
> See any statistic book that covers regression.
>
> http://en.wikipedia.org/wiki/Coefficient_of_determination
>
> > > > SPREAD=5;
> >
> > > Why did you choose this value?
>
> > ------------------> i just put some value, i don't know what
> values should i use? (i thought the best spread is obtained
> > through trial and error method)
>
> True, but why whistle in the dark when you can quickly estimate
> a few charcteristic distances to help limit the search?
>
------------------>how do i estimate characteristic distances to help limit the search? i even do not know what no should i start with.

> > > How does it compare to
> >
> > > 0.5*mean(median(dist(P,P')))?
>
> Typical half-distance between data points. More useful
> when the data points are either cluster centers from a previous
> cluster analysis or data points selected as neurons.
>
> > ---------> do you mean compare this and spread=5?
>
> Yes.
>
> > ------------->btw, 0.5*mean(median(dist(P,P')))=1.0815

-----------> is this some kind of guideline to choose the spread? the spread should be around that value, it is?less or more but not too far away?

> What is it for hidden neurons ?
>
> > > > MN=24; % sample points
> > > > DF=1;
> >
> > > > %net.layers{1}.transferFcn='radbas';
> > > > %net.layers{2}.transferFcn='purelin';
> >
> > > > net=newrb(P,T,GOAL,SPREAD);
> >
> > > [net, tr] = newrb(P,T,GOAL,SPREAD);
> >
> > -----------------> what is the different between the those two?
> >What is the purpose of putting [net,tr]?
>
> tr is the training record
>
> help newrb
> doc newrb
>
> > > > Y=sim(net,P);
> > > > e=T-Y;
> > > > msetrain=mse(e)
> >
> > > compare with tr.perf(end)
>
> > --------------tr.perf(end)=0.0018
>
> > > > --> this is the result:
> > > > NEWRB, neurons = 0, MSE = 0.130203
> >
> > > If N ~ 24, This is not inconsistent with
> > > mean(var(T)) = 0.1359.
>
> > ___________> I'm really sorry, but i truly do not
> understand what do you by If N ~ 24,
> This is not inconsistent with mean(var(T)) = 0.1359
> >
> > ----------------------->how it suppose to be??
>
> If neurons = 0. Then the the output is a constant
> equal to the bias. To minimize SSE, the constant must
> be mean(T). The resulting MSE is (N-1)*var(T)/N
>
---------->forgive me, i still don't understand.
mean(T)=0.5389
mean(var(T)) = 0.1359
MSE i= (N-1)*var(T)/N= 0.1302 so?

--->To minimize SSE, 'the constant' must be mean(T). 'the constant' refer to?

> > > Where is the tabulation for neurons > 0?
> >
> > > > msetrain =
> >
> > > > 0.0018
> >
> > > For how many neurons?
> > > -------------->Number of nodes in hidden layer=2.0000e+000
> >
> > > > why the mse value is different?
> >
> > > Different number of neurons
> > > What is tr.epoch(end)?
> > > ---------> 2
> > > >the mean(var(T)) is 0.1359
> >
> > > MSE(neurons = 0) = (N-1)*mean(var(T'))/N
> > > -------------> owhh..thats why i get the MSE=0.1302
> > > Hope this helps.
> >
> > > Greg
> >
> > ==============> Thanks, I still have some questions.
> >
> > based on your advice, %For newrb, it is desirable to have SSEgoal < SSE00/100
> > SSE00=3.1249
> > SSEm=SSE00/100 %produce 0.0312
> >
> > so i choose my goal 0.0005 % since SSEgoal < SSE00/100. is this right?
>
> I would use 0.02.
>
> Hope this helps.
>
> Greg

On Nov 19, 4:14 am, "aurikel Radzali" <suriar...@gmail.com> wrote:
> Greg Heath <he...@alumni.brown.edu> wrote > > > > size(P) = ?
> > > > minmax(P) = ?
> > > > size(T) = ?
> > > > minmax(T) = ?
>
> > Please answer the questions.
>
> ---->size(P) =3    24
>        size(T) =1  24

MINMAX??

Greg

Greg Heath <heath@alumni.brown.edu> wrote in message <85397222-7dfd-4f31-a3f7-6e2a088e47e9@p33g2000vbn.googlegroups.com>...
> On Nov 19, 4:14?am, "aurikel Radzali" <suriar...@gmail.com> wrote:
> > Greg Heath <he...@alumni.brown.edu> wrote > > > > size(P) = ?
> > > > > minmax(P) = ?
> > > > > size(T) = ?
> > > > > minmax(T) = ?
> >
> > > Please answer the questions.
> >
> > ---->size(P) =3 ? ?24
> > ? ? ? ?size(T) =1 ?24
>
> MINMAX??
>
> Greg

MINMAXP =

     0 1
     0 1
     0 1

MINMAXT =

     0 1

On Nov 19, 4:14 am, "aurikel Radzali" <suriar...@gmail.com> wrote:
> Greg Heath <he...@alumni.brown.edu> wrote in message <f88c4240-7211-4544-9ca1-f5a656845...@f20g2000vbl.googlegroups.com
-----SNIP
> > > > size(P) = ?
> > > > minmax(P) = ?
> > > > size(T) = ?
> > > > minmax(T) = ?
>
> > Please answer the questions.
>
> ---->size(P) =3 24
> size(T) =1 24

MINMAX?

OK [0 1] from a recent reply.

-----SNIP

> > > > > SPREAD=5;
>
> > > > Why did you choose this value?
>
> > > ------------------> i just put some value, i don't know what
> > values should i use? (i thought the best spread is obtained
> > > through trial and error method)

Yes. That is your best bet.

Now that you realize that the input data is contained in a unit cube
it should be obvious the spread = 5 is inappropriate.

> > True, but why whistle in the dark when you can quickly estimate
> > a few charcteristic distances to help limit the search?
>
> ------------------>how do i estimate characteristic distances to help
limit the search? i even do not know what no should i start with
.
What can you tell about the data from N, minmax(P) and summary
statistics of dist(P,P') (exclude the diagonal)?
What if the data was uniformly distributed over the cube?

The input data is only 3-D. Therefore you can obtain 1,2,and
3-D scatter plots.

You can use cluster routines to visualize data groups,

etc

>
> > > > How does it compare to
>
> > > > 0.5*mean(median(dist(P,P')))?
>
> > Typical half-distance between data points. More useful
> > when the data points are either cluster centers from a previous
> > cluster analysis or data points selected as neurons.
>
> > > ---------> do you mean compare this and spread=5?
>
> > Yes.
>
> > > ------------->btw, 0.5*mean(median(dist(P,P')))=1.0815
>
> -----------> is this some kind of guideline to choose the spread?
the spread should be around that value, it is?less or more but not too
far
away?

It depends on the data. Other summary stats or even a histogram of
 the distance matrix maybe enlightening w.r.t. what is a good value
for
spread.

Try to understand why the optimal value is good.


> > What is it for hidden neurons ?
>
> > > > > MN=24; % sample points
> > > > > DF=1;
>
> > > > > %net.layers{1}.transferFcn='radbas';
> > > > > %net.layers{2}.transferFcn='purelin';
>
> > > > > net=newrb(P,T,GOAL,SPREAD);
>
> > > > [net, tr] = newrb(P,T,GOAL,SPREAD);
>
> > > -----------------> what is the different between the those two?
> > >What is the purpose of putting [net,tr]?
>
> > tr is the training record
>
> > help newrb
> > doc newrb
>
> > > > > Y=sim(net,P);
> > > > > e=T-Y;
> > > > > msetrain=mse(e)
>
> > > > compare with tr.perf(end)
>
> > > --------------tr.perf(end)=0.0018
>
> > > > > --> this is the result:
> > > > > NEWRB, neurons = 0, MSE = 0.130203
>
> > > > If N ~ 24, This is not inconsistent with
> > > > mean(var(T)) = 0.1359.
>
> > > ___________> I'm really sorry, but i truly do not
> > understand what do you by If N ~ 24,
> > This is not inconsistent with mean(var(T)) = 0.1359
>
> > > ----------------------->how it suppose to be??
>
> > If neurons = 0. Then the the output is a constant
> > equal to the bias. To minimize SSE, the constant must
> > be mean(T). The resulting MSE is (N-1)*var(T)/N
>
> ---------->forgive me, i still don't understand.
> mean(T)=0.5389
> mean(var(T)) = 0.1359
> MSE i= (N-1)*var(T)/N= 0.1302 so?

It is a consistency check. It also warns you that there
must be a nonzero neuron solution with a much lower MSE.
>
> --->To minimize SSE, 'the constant' must be mean(T).
'the constant' refer to?

Yes

> > > > Where is the tabulation for neurons > 0?
>
> > > > > msetrain =
>
> > > > > 0.0018
>
> > > > For how many neurons?
> > > > -------------->Number of nodes in hidden layer=2.0000e+000

You should be able to tabulate No. of neurons and SSE from tr
and recreate the training plot.

> > > > > why the mse value is different?
>
> > > > Different number of neurons
> > > > What is tr.epoch(end)?
> > > > ---------> 2
> > > > >the mean(var(T)) is 0.1359
>
> > > > MSE(neurons = 0) = (N-1)*mean(var(T'))/N
> > > > -------------> owhh..thats why i get the MSE=0.1302
> > > > Hope this helps.
>
> > > > Greg
>
> > > ==============> Thanks, I still have some questions.
>
> > > based on your advice, %For newrb, it is desirable to have SSEgoal < SSE00/100
> > > SSE00=3.1249
> > > SSEm=SSE00/100 %produce 0.0312
>
> > > so i choose my goal 0.0005 % since SSEgoal < SSE00/100. is this right?
>
> > I would use 0.02.

0.0018 more than fits the bill.

Hope this helps.

GregGreg-