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by Edrisfm » Sat Jan 09, 2010 7:39 pm
Hello Excuse me for my bad English! Subject of my project is prediction soccer competitions at the end of a half league with neural networks. I want use Multy Layer Perceptron(Does it work?!). In my project the network was trained with the statistics of first half of the half league such as : Corners count, Offsides count, Accurate passes count and etc. I'm using two 2D array (input[][] and output[][]) for training the network.Data are stored in a file(-La Liga Statistics-its not completed yet! but the statistics of 2 weeks are ready.). Features for prediction are: TeamNr,Possession,Shoot,ShootOnTarget,Corner,Offside,AccuratePass,BadPass In addition there are 16 features for 2 teams.(16 neuron for first layer) The content of data file is: - Code: Select all
20, 1,Barcelona 2,Valladolid 3,Espanyol 4,Valencia 5,Mallorca 6,Athletic Bilbao 7,Atletico Madrid 8,C.D Numancia 9,Malaga 10,Almeria 11,Deportivo la Curona 12,Real Madrid 13,Osasuna 14,Villarreal 15,Racing santander 16,Sevilla,, 17,Real Betis Balompie,, 18,Recreativo Huelva,, 19,Sporting de gijon,, 20,Getafe,,
TeamNr1,Possession1,Shoot1,ShootOnTarget1,Corner1,Offside1,AccuratePass1,BadPass1,Goal1,TeamNr2,Possession2,Shoot2,ShootOnTarget2,Corner2,Offside2,AccuratePass2,BadPass2,Goal2 --------------------------- 1,,, 3,38,10,2,1,2,160,27,1,2,62,11,1,9,2,312,83,0 4,54,17,6,5,5,340,52,3,5,46,16,2,6,4,284,38,0 6,46,10,4,2,4,215,42,1,10,54,11,5,6,0,266,59,3 7,56,25,9,11,3,306,59,4,9,44,7,2,7,2,210,36,0 8,27,5,2,2,6,150,33,1,1,73,25,5,7,1,501,77,0 11,38,11,3,6,3,250,53,2,12,62,18,4,5,2,426,72,1 13,44,10,1,10,1,197,58,1,14,56,12,3,2,3,288,66,1 15,38,7,2,4,2,222,59,1,16,62,13,4,6,0,422,42,1 17,60,8,2,2,5,331,54,0,18,40,13,6,2,4,189,43,1 19,42,13,2,2,5,216,55,1,20,58,16,9,7,2,322,48,2
2,,, 1,74,18,7,9,7,532,72,1,15,26,2,1,1,3,130,38,1 16,66,26,13,9,1,425,61,4,19,34,13,8,3,0,181,41,3 2,33,9,4,9,1,126,36,2,7,67,19,8,5,4,324,78,1 10,41,12,3,2,0,194,37,2,4,59,11,3,3,4,306,52,2 20,56,25,6,7,0,327,53,0,17,44,16,4,6,1,250,34,0 9,48,11,2,6,2,194,63,0,6,52,11,4,4,2,226,13,0 5,48,11,3,3,1,267,48,1,13,52,14,7,4,3,308,32,1 12,63,19,10,6,6,414,78,4,8,37,12,4,3,3,210,43,3 18,53,8,3,7,0,282,76,0,3,47,4,1,4,4,239,31,1 14,57,19,7,10,2,314,63,1,11,43,6,1,3,6,236,38,0
This is my code for creating and learning the MLP network, but in running time there is an exception. Where is my mistake??? - Code: Select all
ActivationNetwork MlpNetwork = new ActivationNetwork(new SigmoidFunction(), 20, 16, 2); // I think that // the origin of exception is the parametes that I set. BackPropagationLearning teacher = new BackPropagationLearning(MlpNetwork);
// I use the below if(commented) for check the length of input vector but I understood that input.Length is //equal with MlpNetwork.InputsCount /*if (input.Length != MlpNetwork.InputsCount) MessageBox.Show("Not Eq");*/
teacher.RunEpoch(input,output);
The exception said: "Wrong length of the input vector."  You can download my project from below link: http://www.fileden.com/files/2009/6/5/2467593/proj.zipThanks
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Edrisfm
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by thizzleboom » Sun Jan 10, 2010 1:44 am
I think you need to change... - Code: Select all
ActivationNetwork MlpNetwork = new ActivationNetwork(new SigmoidFunction(), 20, 16, 2);
Looks like you are setting the first layer to 20 but want 16 instead.
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thizzleboom
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by Edrisfm » Sun Jan 10, 2010 3:55 am
thizzleboom wrote:I think you need to change... - Code: Select all
ActivationNetwork MlpNetwork = new ActivationNetwork(new SigmoidFunction(), 20, 16, 2);
Looks like you are setting the first layer to 20 but want 16 instead.
thanks I changed the code: - Code: Select all
ActivationNetwork MlpNetwork = new ActivationNetwork(new SigmoidFunction(),16, 2);
Now, there is no exception  . But Where I set the inputs count??the second parameter in ActivaionNetwork constructor is inputs count(in my project is 20 <every week 10 games and 2 weeks = 20>). Isn't it??? ActivationNetwork(function,inputs count, neurons count in layer 1,neurons count in layer 2,...,neurons count in layer N); Isn't this true??
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Edrisfm
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by andrew.kirillov » Sun Jan 10, 2010 11:53 am
Hello, Take a look at documentation - it tell quite clearly how to specify network's input size and number/size of layers.
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andrew.kirillov
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by thizzleboom » Sun Jan 10, 2010 11:10 pm
Edrisfm wrote:thizzleboom wrote:I think you need to change... - Code: Select all
ActivationNetwork MlpNetwork = new ActivationNetwork(new SigmoidFunction(), 20, 16, 2);
Looks like you are setting the first layer to 20 but want 16 instead.
thanks I changed the code: - Code: Select all
ActivationNetwork MlpNetwork = new ActivationNetwork(new SigmoidFunction(),16, 2);
Now, there is no exception  . But Where I set the inputs count??the second parameter in ActivaionNetwork constructor is inputs count(in my project is 20 <every week 10 games and 2 weeks = 20>). Isn't it??? ActivationNetwork(function,inputs count, neurons count in layer 1,neurons count in layer 2,...,neurons count in layer N); Isn't this true??
I think you might need to rethink your network input. You should not give the team id to the network as input.
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thizzleboom
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by Edrisfm » Sun Jan 24, 2010 7:12 pm
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Edrisfm
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by Edrisfm » Sun Jan 24, 2010 7:22 pm
thizzleboom wrote:I think you might need to rethink your network input. You should not give the team id to the network as input.
I think that TeamNr can be useful. Assume that Barcelona has TeamNr=5. Now, Barcelona maybe not good in a game, but we know that Barcelona even can win with the bad statistics. Here TeamNr can cover this. Except this, TeamNr can be a uncertain factor(every feature that are forgotten). Its my idea and I don't know that it is true or false completely!
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Edrisfm
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