Hello Vinay,
Math.h is a standard Include file with C++. If you
have Turbo C, you shall
have a copy of the same. I am including the
same and a couple of other
libraries here for your convenience. Please
copy the same into your
AmiBroker Include
directory.
Cheers
Prashanth
----- Original Message -----
From: "Vinay Gakkhar," <vgakkhar@xxxxxxco.uk>
To:
<amibroker@xxxxxxxxxps.com>
Sent:
Monday, February 18, 2008 7:53 PM
Subject: [amibroker] NEURAL ANALYSIS
IN AMIBROKER
> Thanks for your guidance.
>
> When I
ran Explore in Automatic Analysis, I got this message
>
> Ln:
1, Col: 17 : Error 42, @include failed because the does does not
>
exist: 'Formulas\Include\math.h' (current working directory
is
> 'F:\Pers\Shares\AmiBroker')
>
> Can you
please guide me what to do now?
>
> Best
regards,
>
> vgakkhar
>
> On Mon, 18 Feb 2008
19:36:49 +0530, scourt2000 <stevehite@xxxxxxxxnet>
>
wrote:
>
> >
> > Here is what you seek. Please use
it trading the ER2 e-mini in the
> > U.S. market (I need the
order flow):
> >
> > #include <math.h>
>
> #include <stdlib.h>
> > #include
<iostream>
> > double
input_hidden_weights[5][6]=
> > {
> >
{9.40985654649721e-001, 9.23136985641824e+000, -
> >
2.86994950445746e+000, -1.26803931926022e+000, -
> >
7.70008830456271e+000, 1.25421731000059e+000 },
> >
{3.08886279182467e+000, 5.78057919510794e+000,
> >
1.10741139003555e+001, -3.65436515636221e+000, -
> >
1.46817775035674e+001, 2.22520984659718e+001 },
> >
{1.69160825877441e-001, -9.91646811530742e+000, -
> >
1.05635083282757e+001, 4.25517810226395e+000,
2.50631134577816e+000, -
> > 2.91169885599088e+000
},
> > {-6.47564626574024e-001, -6.79555863835188e+000,
-
> > 4.77495170169956e+000, 1.35029793165373e+000,
2.78079262918906e+000, -
> > 1.90795645602409e+000
},
> > {1.43573516935369e+000,
7.90014107622549e+000,
> > 1.34639286162717e+000,
-4.87454998380292e-001, -
> > 5.75300672778634e+000,
2.44385407464775e+000 }
> > };
> > double
hidden_bias[5]={ -1.72504436049218e+000, -
> >
1.12353474266980e+001, 1.05782985606737e+001,
6.38618458656671e+000, -
> > 4.76099367812151e+000
};
> > double hidden_output_wts[1][5]=
> >
{
> > {4.85655076789677e+000,
5.85365165791789e-001,
> > 3.11879288899187e+000,
-8.48772823147294e+000, -
> > 9.35987517826960e+000
}
> > };
> > double output_bias[1]={
5.51616000361064e+000 };
> > double max_input[6]={
3.02200000000000e-001, 6.05400000000000e-001,
> >
1.81400000000000e-001, 1.59000000000000e-002,
6.06600000000000e-001,
> > 2.43900000000000e-001
};
> > double min_input[6]={ -2.82000000000000e-001,
-8.46700000000000e-
> > 001, -1.95700000000000e-001,
-9.70000000000000e-003, -
> > 5.52700000000000e-001,
-2.45100000000000e-001 };
> > double max_target[1]={
1.35100000000000e-001 };
> > double min_target[1]={
-1.50800000000000e-001 };
> > double input[6];
> >
double hidden[5];
> > double output[1];
> > void
FindMax(double* vec, double* max, long* maxIndex,int len)
> >
{
> > long i;
> > *max = vec[0];
> > *maxIndex
= 0;
> > for(i=1; i<len; i++)
> > {
> >
if(vec[i]>*max)
> > {
> > *max = vec[i];
> >
*maxIndex = i;
> > }
> > }
> > }
> >
void FindMin(double* vec, double* min, long* minIndex,int len)
>
> {
> > long i;
> > *min = vec[0];
> >
*minIndex = 0;
> > for(i=1; i<len; i++)
> > {
>
> if(vec[i]<*min)
> > {
> > *min = vec[i];
>
> *minIndex = i;
> > }
> > }
> > }
>
> void ScaleInputs(double* input, double min, double max, int
size)
> > {
> > double delta;
> > long
i;
> > for(i=0; i<size; i++)
> > {
> > delta
= (max-min)/(max_input[i]-min_input[i]);
> >
input[i] = min - delta*min_input[i]+ delta*input[i];
>
> }
> > }
> > void UnscaleTargets(double*
output, double min, double max, int size)
> > {
> >
double delta;
> > long i;
> > for(i=0; i<size;
i++)
> > {
> > delta =
(max-min)/(max_target[i]-min_target[i]);
> >
output[i] = (output[i] - min + delta*min_target[i])/delta;
>
> }
> > }
> > double logistic(double x)
> >
{
> > if(x > 100.0) x = 1.0;
> > else if (x <
-100.0) x = 0.0;
> > else x = 1.0/(1.0+exp(-x));
>
> return x;
> > }
> > void
ComputeFeedForwardSignals(double* MAT_INOUT,double*
V_IN,double*
> > V_OUT, double* V_BIAS,int size1,int size2,int
layer)
> > {
> > int row,col;
> > for(row=0;row
< size2; row++)
> > {
> >
V_OUT[row]=0.0;
> >
for(col=0;col<size1;col++)V_OUT[row]+=(*(MAT_INOUT+(row*size1)+col)
>
> *V_IN[col]);
> > V_OUT[row]+=V_BIAS[row];
>
> if(layer==0) V_OUT[row] = logistic(V_OUT[row]);
> >
if(layer==1) V_OUT[row] = tanh(V_OUT[row]);
> > }
>
> }
> > void RunNeuralNet_Regression ()
> >
{
> > ComputeFeedForwardSignals((double*)
> >
input_hidden_weights,input,hidden,hidden_bias,6,
5,0);
> > ComputeFeedForwardSignals((double*)
>
> hidden_output_wts,hidden,output,output_bias,5,
1,1);
> > }
> >
> >
> >
>
>
> >
> >
> > --- In amibroker@xxxxxxxxxps.com,
"Vinay Gakkhar," <vgakkhar@xx.>
> > wrote:
>
>>
> >> Dear Prashanth, Dear Ton, Dear John,
>
>>
> >> This is with reference to my following request
of 5th Oct 2007 to
> >> Prashanth, and your following
interaction.
> >>
> >> Can i have the AFL John had
posted in this forum on 23rd Sept,
> > 2007, which
>
>> was reproduced by Prashanth in his reply to Ton on 6th October
,
> > 2007 ? I
> >> have not been able to locate
it.
> >>
> >> Best regards,
>
>>
> >> Vinay
> >>
> >>
>
>> Re: [amibroker] NEURAL ANALYSIS IN AMIBROKER
>
>>
> >> Ton Sieverding
> >> Sat, 06 Oct 2007
12:07:16 -0700
> >>
> >> Thanks John. Most
important part for me is to hear that you got AB
> >
running
> >> a
> >> NN. Please let me know the
Intermaket data you were using. Also
> > what's the
>
>> learning procedure for the NN ? In other words, can you please
give
> > us a
> >> little
> >> more
background music ?
> >>
> >> Regards, Ton.
>
>>
> >> ----- Original Message -----
> >>
From: [EMAIL PROTECTED]
> >> To: amibroker@xxxxxxxxxps.com
>
>> Sent: Saturday, October 06, 2007 11:05 AM
> >>
Subject: Re: [amibroker] NEURAL ANALYSIS IN AMIBROKER
>
>>
> >> PLease bare in mind that this is only the source
code to the NN
> > in C++
> >> You would still need
to create the function and feed data in.
> >> Thsi network is
based on an example network i built a while
> > back to
>
>> predict
> >> the log return of the Aussie Dollar
futures contract over the next
> > 50
> >> days.
It
> >> needs to be fed the log returns of 6 intermarkets to
provide a
> > relevant
> >> output.
> >>
the reason i posted the code was not so someone could use it as
>
> a NN, but
> >> to
> >> emphasise teh fact
that a NN built using a 3rd party tool COULD be
> >>
integrated
> >> into AB using ADK and used in a trading
system.
> >>
> >> John
> >>
>
>> Prashanth <[EMAIL PROTECTED]> wrote:
> >> Hello
Ton,
> >>
> >> Attached is the AFL that a person
by name John had posted in
> > this
> >> forum
on
> >> 23-09-07.
> >>
> >>
Cheers
> >>
> >> Prashanth
>
>>
> >> ----- Original Message -----
> >>
From: "Ton Sieverding" <[EMAIL PROTECTED]>
> >> To:
<amibroker@xxxxxxxxxps.com>
>
>> Sent: Saturday, October 06, 2007 12:11 AM
> >>
Subject: Re: [amibroker] NEURAL ANALYSIS IN AMIBROKER
>
>>
> >> > Prashanth do you still know where to find
the code for a
> > NN ? I
> >> really
>
>> would
> >> > like to see how this works because I
just don't understand
> > what AB
> >> has to
>
>> do
> >> > with NN ...
> >>
>
> >> > Regards, Ton.
> >> >
>
>> > ----- Original Message -----
> >> > From:
"Prashanth" <[EMAIL PROTECTED]>
> >> > To: <amibroker@xxxxxxxxxps.com>
>
>> > Sent: Friday, October 05, 2007 7:49 PM
> >> >
Subject: Re: [amibroker] NEURAL ANALYSIS IN AMIBROKER
> >>
>
> >> >
> >> > > Hello Vinay,
>
>> > >
> >> > > I think this question of you
rs was answered a while
> > back. As far
> >> as
my
> >> > > belief and knowledge is concerned, No, you
cant create a
> > Neural
> >> Network
>
>> > > using just AB.
> >> > >
>
>> > > Someone had posted a formula which he said that
proved
> > that NN can
> >> infact
> >>
> be
> >> > > coded in AB, but since my C++ files
have a compliation
> > error, I
> >> havent
>
>> > been
> >> > > able to test out the
same.
> >> > >
> >> > > There are a
lot of NN based trading products in the
> > market though
>
>> I am
> >> not
> >> > > sure as to
whether they really can make money for the
> > buyer
since
> >> if it
> >> > > could, it woudnt
be for sale in the first place.
> >> > >
>
>> > > Cheers
> >> > >
> >> >
> Prashanth
> >> > >
> >> > > -----
Original Message -----
> >> > > From: "Vinay Gakkhar."
<[EMAIL PROTECTED]>
> >> > > To: "amibroker"
<amibroker@xxxxxxxxxps.com>
>
>> > > Sent: Friday, October 05, 2007 3:40 PM
> >>
> > Subject: [amibroker] NEURAL ANALYSIS IN AMIBROKER
>
>> > >
> >> > >
> >> > >
> Dear Prashanth,
> >> > > >
> >> >
> > Can you please tell me whether there is any formula or
>
> add-on
> >> for
> >> > > > Amibroker
which analyses the available past data like a
> > neural
>
>> network
> >> > > > does, finds the common
pattern, and shows the result
> > like neural
> >>
> network?
> >> > > >
> >> > >
> Thanks,
> >> > > >
> >> > >
> vinay
> >>
> >
>
>
>
>
>
> Please note that this group is for
discussion between users only.
>
> To get support from
AmiBroker please send an e-mail directly to
> SUPPORT {at}
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>
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