ISmSelfOrganizingMap.FinalWeights

Syntax

FinalWeights: Array;

Description

The FinalWeights property returns the matrix of final synapse weights.

Comments

To determine the matrix of synapse weights, use the ISmSelfOrganizingMap.InitialWeights property.

Example

To execute the example, add links to the Stat and MathFin system assemblies.

Sub UserProc;
Var
    som: ISmSelfOrganizingMap;
    x1, w, min, max: array Of double;
    res, i, j, m, n: integer;
    indx0: double;
Begin
    som := New SmSelfOrganizingMap.Create;
    m := 2; //object size
    n := 4; //number of clusters
    som.Objects.Clear;
    x1 := New double[m];
    //adding characteristics, in this case 12 objects with two characteristics
    x1[0] := 27; x1[1] := 19;
    som.Objects.Add.Value := x1;
    x1[0] := Double.Nan; x1[1] := Double.Nan;
    som.Objects.Add.Value := x1;
    x1[0] := 25; x1[1] := 15;
    som.Objects.Add.Value := x1;
    x1[0] := 36; x1[1] := 27;
    som.Objects.Add.Value := x1;
    x1[0] := 35; x1[1] := 25;
    som.Objects.Add.Value := x1;
    x1[0] := 10; x1[1] := 43;
    som.Objects.Add.Value := x1;
    x1[0] := 11; x1[1] := 44;
    som.Objects.Add.Value := x1;
    x1[0] := 36; x1[1] := 24;
    som.Objects.Add.Value := x1;
    x1[0] := 26; x1[1] := 14;
    som.Objects.Add.Value := x1;
    x1[0] := 26; x1[1] := 14;
    som.Objects.Add.Value := x1;
    x1[0] := 9; x1[1] := 45;
    som.Objects.Add.Value := x1;
    x1[0] := 33; x1[1] := 23;
    som.Objects.Add.Value := x1;
    x1[0] := 27; x1[1] := 16;
    som.Objects.Add.Value := x1;
    x1[0] := 10; x1[1] := 47;
    som.Objects.Add.Value := x1;
    som.ClusterCount := 3;
    som.Epoch := 10;
    // network size
    som.RowWidth := 2;
    // Method of missing data treatment
    som.MissingData.Method := MissingDataMethod.Casewise;
    min := New Double[m];
    max := New Double[m];
    For j := 0 To m - 1 Do
        min[j] := som.Objects.Item(0).Value[j];
        max[j] := som.Objects.Item(0).Value[j];
    End For;
    For i := 1 To som.Objects.Count - 1 Do
        For j := 0 To m - 1 Do
            If som.Objects.Item(i).Value[j] < min[j] Then min[j] := som.Objects.Item(i).Value[j]; End If;
            If som.Objects.Item(i).Value[j] > max[j] Then max[j] := som.Objects.Item(i).Value[j]; End If;
        End For;
    End For;
    W := New double[som.ClusterCount, m];
    For i := 0 To som.ClusterCount - 1 Do
        For j := 0 To m - 1 Do
            W[i, j] := 1 / math.Sqrt(m);
        End For;
    End For;
    // specify weights
    som.SynapsysWeights := SynapsysWeightsType.Manual;
    som.InitialWeights := w;
    res := som.Execute;
    Debug.WriteLine(som.Errors);
    Debug.WriteLine("Matrix of synapse weights");
    Debug.Indent;
    For i := 0 To som.ClusterCount - 1 Do // by clusters
        Debug.WriteLine("Node # + i.ToString);
        For j := 0 To som.Clusters.Item(i).Center.Length - 1 Do // by all objects in cluster
            indx0 := som.InitialWeights[i, j];
            Debug.WriteLine(indx0.ToString + ", ");
        End For;
        Debug.WriteLine("");
    End For;
    Debug.Unindent;
    Debug.WriteLine("Total weights");
    Debug.Indent;
    For i := 0 To som.ClusterCount - 1 Do // by clusters
        Debug.WriteLine("Node # + i.ToString);
        For j := 0 To som.Clusters.Item(i).Center.Length - 1 Do // by all objects in cluster
            indx0 := som.FinalWeights[i, j];
            Debug.WriteLine(indx0.ToString + ", ");
        End For;
        Debug.WriteLine("");
    End For;
    Debug.Unindent;
End Sub UserProc;

After executing the example the console window displays the matrix of weights and total weights.