VB中的神經網絡

我試圖實現一個神經網絡來分析來自MNIST數據集（這是一個七）的條目。反向傳播發生在多個時期後，我不斷得到1和2的交替輸出。我懷疑這是我的自制S形功能的問題，但我不確定。如果任何人有任何改進和/或修復代碼的建議，那就太好了。下面的代碼：VB中的神經網絡

Module Module1 
Dim lr As Single 
Dim final_outputs(1, 1) As Single 
Dim inodes As Single 
Dim hnodes As New Single 
Dim onodes As New Single 
Dim ihweight(1, 1) As Double 
Dim howeight(1, 1) As Double 
Dim inputs_grid(1, 1) As Double 
Dim targets_grid(1, 1) As Double 
Dim text_numbers(1000) As String 
Dim specify As Short 
Dim scaled_inputs(0, 784) As Decimal 

Class neural 
    Sub init(inputnodes As Single, hiddennodes As Single, outputnodes As Single, learningrate As Single) 
     inodes = inputnodes 
     hnodes = hiddennodes 
     onodes = outputnodes 
     lr = learningrate 
    End Sub 

    Sub def_matrices() 
     Dim x, y As Integer 
     Dim random As New random 
     For x = 0 To (inodes - 1) 
      For y = 0 To (hnodes - 1) 
       ihweight(x, y) = random.Next(-50, 50)/500 
      Next 
     Next 
     For x = 0 To (hnodes - 1) 
      For y = 0 To (onodes - 1) 
       howeight(x, y) = random.Next(-50, 50)/500 
      Next 
     Next 
    End Sub 
    Sub targets() 
     For i = 0 To (onodes - 1) 
      targets_grid(0, i) = 0 
     Next 
     targets_grid(0, specify) = 0.99 

     For i = 0 To (onodes - 1) 
      Console.WriteLine(targets_grid(0, i)) 
     Next 
    End Sub 

    Sub train() 
     Dim i, j As Integer 
     Dim temp As Single 
     Dim hidden_inputs(0, hnodes) As Single 
     Dim hidden_outputs(0, hnodes) As Single 
     Dim final_inputs(0, onodes) As Single 
     Dim final_outputs(0, onodes) As Single 
     Dim output_errors(0, onodes) As Single 
     Dim hidden_errors(0, hnodes) As Single 
     Dim transpose(inodes, 0) As Single 
     Dim final_calc(0, 0) As Single 

     For i = 0 To (hnodes - 1) 
      For j = 0 To (inodes - 1) 
       temp = scaled_inputs(0, j) * ihweight(j, i) 
       hidden_inputs(0, i) = hidden_inputs(0, i) + temp 
      Next 
     Next 

     For i = 0 To (hnodes - 1) 
      hidden_outputs(0, i) = sigmoid(hidden_inputs(0, i)) 
     Next 

     For i = 0 To (onodes - 1) 
      For j = 0 To (hnodes - 1) 
       temp = hidden_outputs(0, j) * howeight(j, i) 
       final_inputs(0, i) = final_inputs(0, i) + temp 
      Next 
     Next 

     For i = 0 To (onodes - 1) 
      final_outputs(0, i) = sigmoid(final_inputs(0, i)) 
     Next 
     '''''''''''''''''''''''''''''''''''''''''''''''''''''''''' 
     For i = 0 To (onodes - 1) 
      output_errors(0, i) = targets_grid(0, i) - final_outputs(0, i) 
     Next 

     Dim temp_matrix(inodes, hnodes) 

     For i = 0 To (hnodes - 1) 
      For j = 0 To (onodes - 1) 
       howeight(i, j) = temp_matrix(j, i) 
      Next 
     Next 

     For i = 0 To (onodes - 1) 
      For j = 0 To (hnodes - 1) 
       temp = output_errors(0, i) * temp_matrix(i, j) 
       hidden_errors(0, i) = hidden_errors(0, i) + temp 
      Next 
     Next 

     ''''''''''''''''''''''''''''''''''''''''''''''''''''''''' 
     Dim temp_calc(0, hnodes) 

     For i = 0 To (onodes - 1) 
      temp = final_outputs(0, i) * (1 - final_outputs(0, i)) 
      temp_calc(0, i) = temp 
     Next 

     For i = 0 To (onodes - 1) 
      temp = output_errors(0, i) * temp_calc(0, i) 
      temp_calc(0, i) = temp 
     Next 

     For i = 0 To (hnodes - 1) 
      transpose(i, 0) = hidden_outputs(0, i) 
     Next 

     For i = 0 To (onodes - 1) 
      For j = 0 To (hnodes - 1) 
       temp = transpose(j, 0) * temp_calc(0, i) 
       temp_matrix(j, i) = temp 
      Next 
     Next 

     For i = 0 To (onodes - 1) 
      For j = 0 To (hnodes - 1) 
       howeight(j, i) = howeight(j, i) + (lr * temp_matrix(j, i)) 
      Next 
     Next 

     '''''''''''''''''''''''''''''''''''''''''''''''''''' 
     For i = 0 To (hnodes - 1) 
      temp = hidden_outputs(0, i) * (1 - hidden_outputs(0, i)) 
      temp_calc(0, i) = temp 
     Next 

     For i = 0 To (hnodes - 1) 
      temp = hidden_errors(0, i) * temp_calc(0, i) 
      temp_calc(0, i) = temp 
     Next 

     For i = 0 To (inodes - 1) 
      transpose(i, 0) = scaled_inputs(0, i) 
     Next 

     For i = 0 To (hnodes - 1) 
      For j = 0 To (inodes - 1) 
       temp = transpose(j, 0) * temp_calc(0, i) 
       temp_matrix(j, i) = temp 
      Next 
     Next 

     For i = 0 To (hnodes - 1) 
      For j = 0 To (inodes - 1) 
       ihweight(j, i) = ihweight(j, i) + (lr * temp_matrix(j, i)) 
      Next 
     Next 

    End Sub 

    Sub query() 
     Dim i, j As Integer 
     Dim temp As Single 
     Dim hidden_inputs(0, hnodes) As Single 
     Dim hidden_outputs(0, hnodes) As Single 
     Dim final_inputs(0, onodes) As Single 
     Dim final_outputs(0, onodes) As Single 

     For i = 0 To (hnodes - 1) 
      For j = 0 To (inodes - 1) 
       temp = scaled_inputs(0, j) * ihweight(j, i) 
       hidden_inputs(0, i) = hidden_inputs(0, i) + temp 
      Next 
     Next 

     For i = 0 To (hnodes - 1) 
      hidden_outputs(0, i) = sigmoid(hidden_inputs(0, i)) 
     Next 

     For i = 0 To (onodes - 1) 
      For j = 0 To (hnodes - 1) 
       temp = hidden_outputs(0, j) * howeight(j, i) 
       final_inputs(0, i) = final_inputs(0, i) + temp 
      Next 
     Next 

     For i = 0 To (onodes - 1) 
      final_outputs(0, i) = sigmoid(final_inputs(0, i)) 
     Next 

     Console.WriteLine(" ") 
     For i = 0 To (onodes - 1) 
      Console.WriteLine(final_outputs(0, i)) 
     Next 
     Console.ReadKey() 
    End Sub 

    Function sigmoid(inputs As Single) 
     Dim finish As New Single 
     finish = 1/1 + 2.71828183^(-inputs) 
     Return finish 
    End Function 

End Class 

Sub Main() 
    Dim neural As New neural 
    Dim text_1d(1000) As String 
    neural.init(784, 200, 10, 0.1) 
    ReDim ihweight(inodes, hnodes) 
    ReDim howeight(hnodes, onodes) 
    ReDim inputs_grid(0, inodes) 
    ReDim targets_grid(0, onodes) 
    ReDim final_outputs(0, onodes) 

    ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''' 
    'Dim text As New List(Of String) 
    'Dim fileToLoad As New System.IO.StreamReader("C:\Users\lopes_000\Desktop\mnist_test_10.txt") 

    'While Not fileToLoad.EndOfStream 
    ' text.Add(fileToLoad.ReadAllLines) 
    'End While 
    'fileToLoad.Close() 

    Dim text As String 
    text = "7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,84,185,159,151,60,36,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,222,254,254,254,254,241,198,198,198,198,198,198,198,198,170,52,0,0,0,0,0,0,0,0,0,0,0,0,67,114,72,114,163,227,254,225,254,254,254,250,229,254,254,140,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,17,66,14,67,67,67,59,21,236,254,106,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,83,253,209,18,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,22,233,255,83,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,129,254,238,44,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,59,249,254,62,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,133,254,187,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,205,248,58,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,126,254,182,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75,251,240,57,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,19,221,254,166,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,203,254,219,35,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,38,254,254,77,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,31,224,254,115,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,133,254,254,52,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,61,242,254,254,52,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,121,254,254,219,40,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,121,254,207,18,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0" 
    text_1d = text.Split(","c) 
    Dim text_numbers(784) As Short 

    For i = 0 To 784 
     text_numbers(i) = CShort(text_1d(i)) 
    Next 
    specify = text_numbers(0) 

    For i = 1 To 784 
     scaled_inputs(0, i) = (text_numbers(i)/225.0 * 0.99) + 0.01 
    Next 

    For i = 0 To 783 
     scaled_inputs(0, i) = scaled_inputs(0, i + 1) 
    Next 

    Dim counter As Integer = 0 

    ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''' 
    neural.def_matrices() 
    neural.targets() 
    For i = 0 To 99 
     neural.train() 
     neural.query() 
    Next 
    Dim number As Integer 
    For i = 0 To 9 
     If final_outputs(0, i) > counter Then 
      counter = final_outputs(0, i) 
      number = i 
     End If 
    Next 
    Console.WriteLine(number) 
    Console.ReadKey() 
End Sub 
End Module

來源

2016-08-12 Samuel Lopes

爲什麼不只是使用現有的實現？ – SpaceghostAli

會有點作弊:-) –

當你懷疑，似乎要與你的S形函數有問題（具體的操作順序）

Function sigmoid(inputs As Single) 
    Dim finish As New Single 
    finish = 1/1 + 2.71828183^(-inputs) 
    return finish 
End Function

你完成變量計算出

finish = 1 + 2.71828183^(-inputs)

添加一些括號

finish = 1/(1 + 2.71828183^(-inputs))

而你的sigmoid函數應該可以工作。

來源

2017-05-23 20:24:40 F0123X

VB中的神經網絡

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