CorrectPrediction: Integer;
The CorrectPrediction property determines the number of correctly predicted values.
This example describes setting calculation parameters for the Binary Regression method.
Sub Main;
Var
bm: SmBinaryModel;
can: Array Of Double;
bin2: Array Of Integer;
i, res, mm: Integer;
Intercept: IIntercept;
Explanatories: ISlSeries;
GuessingTable: ISlQualityTable;
GuessTableItem: ISlQualitySet;
Begin
// Specify explanatory series values
can := New double[9];
can[00] := 6.209; can[05] := 5;
can[01] := 6.385; can[06] := 6;
can[02] := 6.29; can[07] := 7;
can[03] := 6.25; can[08] := 8;
can[04] := 6.1;
// Specify explained series values
bin2 := New integer[5];
bin2[00] := 1; bin2[03] := 0;
bin2[01] := 1; bin2[04] := 0;
bin2[02] := 0;
bm := New SmBinaryModel.Create;
// Specify values for the first and the last sample period points
bm.ModelPeriod.FirstPoint := 1;
bm.ModelPeriod.LastPoint := 5;
// Specify value of the last forecast point
bm.Forecast.LastPoint := 14;
// Specify method of constant estimation
Intercept := bm.ModelCoefficients.Intercept;
Intercept.Mode := InterceptMode.AutoEstimate;
// Specify method of missing data treatment
bm.MissingData.Method := MissingDataMethod.SampleAverage;
// Specify model type
bm.BinaryDistr := BinaryDistrType.Probit;
// Set value for group division and accuracy
bm.ClassificationCutOff := 0.5;
bm.Tolerance := 0.001;
// Specify explained series
bm.BinaryExplained := bin2;
// Specify explanatory series
Explanatories := bm.Explanatories;
Explanatories.Add.Value := can;
Explanatories.Item(0).Include := True;
// Perform calculations and show error messages
bm.Execute;
Debug.WriteLine(bm.Errors);
// Show calculation results
If (res = 0) Then
// Table of binary model selection quality
Debug.WriteLine("Description of selection quality");
GuessingTable := bm.GuessingTable;
For mm := 0 To 1 Do
GuessTableItem := GuessingTable.Item(mm);
i := GuessTableItem.Actual;
Debug.WriteLine(mm.ToString + ". Fact: " + i.ToString);
i := GuessTableItem.Prediction;
Debug.WriteLine(mm.ToString + ". Predicted: " + i.ToString);
i := GuessTableItem.CorrectPrediction;
Debug.WriteLine(mm.ToString + ". Predicted correctly: " + i.ToString);
End For;
End If;
End Sub Main;
After executing the example calculation parameters are set. The console window displays calculation results and values describing quality of binary model selection:
Module execution started
No errors
Selection quality description
0. Fact: 3
0. Predicted: 3
0. Predicted correctly: 2
1. Fact: 2
1. Predicted: 2
1. Predicted correctly: 1
Module execution finished
See also: