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system 9.2 Update 9 of 11/09/2020,
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FORESIGHT
Tree: IBinaryTreeNode;
Tree: Prognoz.Platform.Interop.Stat.IBinaryTreeNode;
The Tree property returns the created decision tree.
A decision tree is a hierarchical tree of rules, where each object corresponds to a single node giving the decision. A rule is a logical construction represented as "if... then ...".
To execute the example add links to the Stat system assembly.
Public Sub UserProc;
Var
CART: SmCART;
y: Array[16] Of Integer;
x1: Array[16] Of Integer;
x2: Array[16] Of Integer;
x3dbl: array[16] Of double;
x4cat: array[16] Of integer;
TreeSizeSpecification: ITreeSpecification;
res: integer;
i: integer;
str: string;
d: double;
CatList: Array Of Integer;
Begin
// Create object to calculate classification tree
CART := New SmCART.Create;
// Set explained series values
y[0] := 1000; y[4] := 201; y[8] := -1; y[12] := 5002;
y[1] := 1000; y[5] := 201; y[9] := 5002; y[13] := 5002;
y[2] := 1000; y[6] := 201; y[10] := 5002; y[14] := -1;
y[3] := 1000; y[7] := 201; y[11] := 5002; y[15] := 5002;
// Set value of explanatory ordinal series x1
x1[0] := 0; x1[4] := 0; x1[8] := 0; x1[12] := 1;
x1[1] := 0; x1[5] := 0; x1[9] := 1; x1[13] := 1;
x1[2] := 0; x1[6] := 0; x1[10] := 1; x1[14] := 1;
x1[3] := 0; x1[7] := 0; x1[11] := 1; x1[15] := 1;
// Set value of explanatory ordinal series x2
x2[0] := 10; x2[4] := 10; x2[8] := 20; x2[12] := 20;
x2[1] := 10; x2[5] := 20; x2[9] := 10; x2[13] := 20;
x2[2] := 10; x2[6] := 20; x2[10] := 10; x2[14] := 20;
x2[3] := 10; x2[7] := 20; x2[11] := 20; x2[15] := 20;
// Set values of explanatory quantitative series
x3dbl[0] := 1; x3dbl[4] := 4; x3dbl[8] := 9; x3dbl[12] := 11;
x3dbl[1] := 2; x3dbl[5] := 6; x3dbl[9] := 9; x3dbl[13] := 12;
x3dbl[2] := 3; x3dbl[6] := 7; x3dbl[10] := 10; x3dbl[14] := 13;
x3dbl[3] := 5; x3dbl[7] := 8; x3dbl[11] := 10; x3dbl[15] := 14;
// Set values of explanatory categorical series
x4cat[0] := 1; x4cat[4] := 1; x4cat[8] := 2; x4cat[12] := 3;
x4cat[1] := 1; x4cat[5] := 1; x4cat[9] := 2; x4cat[13] := 3;
x4cat[2] := 1; x4cat[6] := 1; x4cat[10] := 2; x4cat[14] := 3;
x4cat[3] := 1; x4cat[7] := 2; x4cat[11] := 2; x4cat[15] := 3;
// Set parameters describing tree
TreeSizeSpecification := CART.TreeSizeSpecification;
TreeSizeSpecification.MaximumNumberOfLevels := 10;
TreeSizeSpecification.MinimumNumberOfCases := 2;
// Set explained series
CART.Dependent.Value := y;
// Set explanatory ordinal series
CART.ExplanatoriesOrdered.Add.Value := x1;
CART.ExplanatoriesOrdered.Add.Value := x2;
// Set explanatory quantitative series
cart.ExplanatoriesContinuous.Add.Value := x3dbl;
// Set explanatory categorical series
CART.ExplanatoriesCategorical.Add.Value := x4cat;
// Execute calculation
res := CART.Execute;
If res <> 0 Then
Debug.WriteLine("An error occurred");
Debug.WriteLine(CART.Errors);
// If calculation is executed without errors, display results
Else
Debug.WriteLine("Initial values - processed values:");
Debug.Indent;
For i := 0 To CART.Dependent.Value.Length - 1 Do
str := i.ToString + ": ";
d := CART.Dependent.Value[i];
str := str + d.ToString + " - ";
d := CART.FilledDependent[i];
str := str + d.ToString + " ";
Debug.WriteLine(str);
End For;
Debug.Unindent;
// Display list of categories
CatList := CART.CategoriesList;
If CatList.Length > 0 Then
Debug.WriteLine("List of categories:");
Debug.Indent;
For i := 0 To CatList.Length - 1 Do
Debug.WriteLine(CatList[i]);
End For;
Debug.Unindent;
End If;
// Display decision tree
Debug.WriteLine("Decision tree:");
print(CART.Tree);
End If;
End Sub UserProc;
// Procedure of outputting decision tree
Sub print(node: IBinaryTreeNode);
Var
i: Integer;
Categorical: Boolean = False;
Begin
Debug.Indent;
Debug.WriteLine("Node number: " + node.NodeIndex.ToString);
Debug.WriteLine("Improvement: " + node.Improvement.ToString);
Debug.WriteLine("Number of cases in node: " + node.Total.ToString);
Debug.WriteLine("Criterion index: " + node.ExplanatorieIndex.ToString);
Debug.WriteLine("Criterion name: " + node.Name);
Debug.Write("Criterion type: ");
Select Case node.PropertyType
Case
DecisionTreePropertyType.Categorical: Debug.WriteLine("categorical");
Categorical := True;
Case DecisionTreePropertyType.NoProperty: Debug.WriteLine("-");
Case DecisionTreePropertyType.Ordered: Debug.WriteLine("ordinal");
Case DecisionTreePropertyType.Value: Debug.WriteLine("quantitative");
End Select;
If Not Categorical Then
Debug.WriteLine("Criterion value: " + node.Value.ToString);
End If;
If (node.LeftNode <> Null) Then
Debug.WriteLine("Left branch: ");
print(node.LeftNode);
End If;
If (node.LeftNodeCategories.Length <> 0) And Categorical Then
Debug.WriteLine("List of categories which are sorted to the left branch: ");
For i := 0 To node.LeftNodeCategories.Length - 1 Do
Debug.WriteLine(node.LeftNodeCategories[i]);
End For;
End If;
If (node.RightNode <> Null) Then
Debug.WriteLine("Right branch: ");
print(node.RightNode);
End If;
If (node.RightNodeCategories.Length <> 0) And Categorical Then
Debug.WriteLine("List of categories which are sorted to the right branch: ");
For i := 0 To node.RightNodeCategories.Length - 1 Do
Debug.WriteLine(node.RightNodeCategories[i]);
End For;
End If;
Debug.Unindent;
End Sub print;
After executing the example task will be calculated using classification tree.Calculation results are displayed to the browser console.
The requirements and result of the Fore.NET example execution match with those in the Fore example.
Imports Prognoz.Platform.Interop.Stat;
…
Public Shared Sub Main(Params: StartParams);
Var
CART: SmCART;
y: Array[16] Of integer;
x1: Array[16] Of integer;
x2: Array[16] Of Integer;
x3dbl: array[16] Of double;
x4cat: array[16] Of integer;
TreeSizeSpecification: ITreeSpecification;
res: integer;
i: integer;
str: string;
CatList, Value: System.Array;
Begin
// Create object to calculate classification tree
CART := New SmCART.Create();
// Set explained series values
y[0] := 1000; y[4] := 201; y[8] := -1; y[12] := 5002;
y[1] := 1000; y[5] := 201; y[9] := 5002; y[13] := 5002;
y[2] := 1000; y[6] := 201; y[10] := 5002; y[14] := -1;
y[3] := 1000; y[7] := 201; y[11] := 5002; y[15] := 5002;
// Set value of explanatory ordinal series x1
x1[0] := 0; x1[4] := 0; x1[8] := 0; x1[12] := 1;
x1[1] := 0; x1[5] := 0; x1[9] := 1; x1[13] := 1;
x1[2] := 0; x1[6] := 0; x1[10] := 1; x1[14] := 1;
x1[3] := 0; x1[7] := 0; x1[11] := 1; x1[15] := 1;
// Set value of explanatory ordinal series x2
x2[0] := 10; x2[4] := 10; x2[8] := 20; x2[12] := 20;
x2[1] := 10; x2[5] := 20; x2[9] := 10; x2[13] := 20;
x2[2] := 10; x2[6] := 20; x2[10] := 10; x2[14] := 20;
x2[3] := 10; x2[7] := 20; x2[11] := 20; x2[15] := 20;
// Set values of explanatory quantitative series
x3dbl[0] := 1; x3dbl[4] := 4; x3dbl[8] := 9; x3dbl[12] := 11;
x3dbl[1] := 2; x3dbl[5] := 6; x3dbl[9] := 9; x3dbl[13] := 12;
x3dbl[2] := 3; x3dbl[6] := 7; x3dbl[10] := 10; x3dbl[14] := 13;
x3dbl[3] := 5; x3dbl[7] := 8; x3dbl[11] := 10; x3dbl[15] := 14;
// Set values of explanatory categorical series
x4cat[0] := 1; x4cat[4] := 1; x4cat[8] := 2; x4cat[12] := 3;
x4cat[1] := 1; x4cat[5] := 1; x4cat[9] := 2; x4cat[13] := 3;
x4cat[2] := 1; x4cat[6] := 1; x4cat[10] := 2; x4cat[14] := 3;
x4cat[3] := 1; x4cat[7] := 2; x4cat[11] := 2; x4cat[15] := 3;
// Set parameters describing tree
TreeSizeSpecification := CART.TreeSizeSpecification;
TreeSizeSpecification.MaximumNumberOfLevels := 10;
TreeSizeSpecification.MinimumNumberOfCases := 2;
// Set explained series
CART.Dependent.Value := y;
// Set explanatory ordinal series
CART.ExplanatoriesOrdered.Add().Value := x1;
CART.ExplanatoriesOrdered.Add().Value := x2;
// Set explanatory quantitative series
cart.ExplanatoriesContinuous.Add().Value := x3dbl;
// Set explanatory categorical series
CART.ExplanatoriesCategorical.Add().Value := x4cat;
// Execute calculation
res := CART.Execute();
If res <> 0 Then
System.Diagnostics.Debug.WriteLine("An error occurred");
System.Diagnostics.Debug.WriteLine(CART.Errors);
// If calculation is executed without errors, display results
Else
System.Diagnostics.Debug.WriteLine("Initial values - processed values:");
System.Diagnostics.Debug.Indent();
Value := CART.Dependent.Value;
For i := 0 To CART.Dependent.Value.Length - 1 Do
str := i.ToString() + ": ";
str := str + Value[i].ToString() + " - ";
str := str + CART.FilledDependent.GetValue(i).ToString() + " ";
System.Diagnostics.Debug.WriteLine(str);
End For;
System.Diagnostics.Debug.Unindent();
// Display list of categories
CatList := CART.CategoriesList;
If CatList.Length > 0 Then
System.Diagnostics.Debug.WriteLine("List of categories:");
System.Diagnostics.Debug.Indent();
For i := 0 To CatList.Length - 1 Do
System.Diagnostics.Debug.WriteLine(CatList[i]);
End For;
System.Diagnostics.Debug.Unindent();
End If;
// Display decision tree
System.Diagnostics.Debug.WriteLine("Decision tree:");
print(CART.Tree);
End If;
End Sub;
// Procedure of outputting decision tree
Public Shared Sub print(node: IBinaryTreeNode);
Var
i: Integer;
Categorical: Boolean = False;
Begin
System.Diagnostics.Debug.Indent();
System.Diagnostics.Debug.WriteLine("Node number: " + node.NodeIndex.ToString());
System.Diagnostics.Debug.WriteLine("Improvement: " + node.Improvement.ToString());
System.Diagnostics.Debug.WriteLine("Number of cases in node: " + node.Total.ToString());
System.Diagnostics.Debug.WriteLine("Criterion index: " + node.ExplanatorieIndex.ToString());
System.Diagnostics.Debug.WriteLine("Criterion name: " + node.Name);
System.Diagnostics.Debug.Write("Criterion type: ");
Select Case node.PropertyType
Case
DecisionTreePropertyType.dtptCategorical: System.Diagnostics.Debug.WriteLine("categorical");
Categorical := True;
Case DecisionTreePropertyType.dtptNoProperty: System.Diagnostics.Debug.WriteLine("-");
Case DecisionTreePropertyType.dtptOrdered: System.Diagnostics.Debug.WriteLine("ordinal");
Case DecisionTreePropertyType.dtptValue: System.Diagnostics.Debug.WriteLine("quantitative");
End Select;
If Not Categorical Then
System.Diagnostics.Debug.WriteLine("Criterion value: " + node.Value.ToString());
End If;
If (node.LeftNode <> Null) Then
System.Diagnostics.Debug.WriteLine("Left branch: ");
print(node.LeftNode);
End If;
If (node.LeftNodeCategories.Length <> 0) And Categorical Then
System.Diagnostics.Debug.WriteLine("List of categories which are sorted to the left branch: ");
For i := 0 To node.LeftNodeCategories.Length - 1 Do
System.Diagnostics.Debug.WriteLine(node.LeftNodeCategories.GetValue(i));
End For;
End If;
If (node.RightNode <> Null) Then
System.Diagnostics.Debug.WriteLine("Right branch: ");
print(node.RightNode);
End If;
If (node.RightNodeCategories.Length <> 0) And Categorical Then
System.Diagnostics.Debug.WriteLine("List of categories which are sorted to the right branch: ");
For i := 0 To node.RightNodeCategories.Length - 1 Do
System.Diagnostics.Debug.WriteLine(node.RightNodeCategories.GetValue(i));
End For;
End If;
System.Diagnostics.Debug.Unindent();
End Sub print;
See also: