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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@xxxxxxxxxxx>
To: <amibroker@xxxxxxxxxxxxxxx>
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@xxxxxxxxxxx>
> 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@xxxxxxxxxxxxxxx, "Vinay Gakkhar," <vgakkhar@xxx>
> > 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@xxxxxxxxxxxxxxx
> >> 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@xxxxxxxxxxxxxxx>
> >> 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@xxxxxxxxxxxxxxx>
> >> > 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@xxxxxxxxxxxxxxx>
> >> > > 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} amibroker.com
>
> For NEW RELEASE ANNOUNCEMENTS and other news always check DEVLOG:
> http://www.amibroker.com/devlog/
>
> For other support material please check also:
> http://www.amibroker.com/support.html
>
> Yahoo! Groups Links
>
>
>
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} amibroker.com
For NEW RELEASE ANNOUNCEMENTS and other news always check DEVLOG:
http://www.amibroker.com/devlog/
For other support material please check also:
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