public void Predicted_Button(object sender, RoutedEventArgs e)
{
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(viewModel.GetPMMLPath(pmmlPath));
// Input object as dictionary
var iris = new
{
Sepal_Length = sepallength.Text,
Sepal_Width = sepalwidth.Text,
Petal_Length = petallength.Text,
Petal_Width = petalwidth.Text
};
//Get predicted result
PredictedResult predictedResult = evaluator.GetResult(iris, null);
viewModel.IrisCollection = new ObservableCollection <Iris>();
viewModel.IrisCollection.Add(new Iris()
{
Species = string.Empty,
Setosa_probability = Convert.ToDouble(predictedResult.GetPredictedProbability("setosa")),
Versicolor_probability = Convert.ToDouble(predictedResult.GetPredictedProbability("versicolor")),
Virginica_probability = Convert.ToDouble(predictedResult.GetPredictedProbability("virginica"))
});
//Change of visibility over input and resultant grid
this.InputGrid.Visibility = Visibility.Collapsed;
this.ResultGrid.Visibility = Visibility.Visible;
}
public void Predicted_Button(object sender, RoutedEventArgs e)
{
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(viewModel.GetPMMLPath(pmmlPath));
// Input object as dictionary
var titanic = new
{
pclass = ((ComboBoxItem)PclassCombo.SelectedItem).Content,
parch = parch.Text,
sex = ((ComboBoxItem)GenderCombo.SelectedItem).Content,
sibsp = sibsp.Text,
age = age.Text
};
//Get predicted result
PredictedResult predictedResult = evaluator.GetResult(titanic, null);
viewModel.TitanicCollection = new ObservableCollection <Titanic>();
viewModel.TitanicCollection.Add(new Titanic()
{
Status = string.Empty,
Died_probability = Convert.ToDouble(predictedResult.GetPredictedProbability("died")),
Survived_probability = Convert.ToDouble(predictedResult.GetPredictedProbability("survived"))
});
//Change of visibility over input and resultant grid
this.InputGrid.Visibility = Visibility.Collapsed;
this.ResultGrid.Visibility = Visibility.Visible;
}
public void Predicted_Button(object sender, RoutedEventArgs e)
{
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(viewModel.GetPMMLPath(pmmlPath));
// Input object as dictionary
var breastcancer = new
{
horTh = ((ComboBoxItem)HorthCombo.SelectedItem).Content,
age = age.Text,
menostat = ((ComboBoxItem)MenostatCombo.SelectedItem).Content,
tsize = tsize.Text,
tgrade = ((ComboBoxItem)HorthCombo.SelectedItem).Content,
pnodes = pnodes.Text,
progrec = progrec.Text,
estrec = estrec.Text,
time = time.Text,
};
//Get predicted result
PredictedResult predictedResult = evaluator.GetResult(breastcancer, null);
viewModel.BreastCancerCollection = new ObservableCollection <BreastCancer>();
viewModel.BreastCancerCollection.Add(new BreastCancer()
{
Status = string.Empty,
Censored_probability = Convert.ToDouble(predictedResult.GetPredictedProbability("0")),
Event_probability = Convert.ToDouble(predictedResult.GetPredictedProbability("1"))
});
//Change of visibility over input and resultant grid
this.InputGrid.Visibility = Visibility.Collapsed;
this.ResultGrid.Visibility = Visibility.Visible;
}
/// <summary>
/// Predicts the results for given PMML and CSV file and serialize the results in a CSV file
/// </summary>
public Table PredictResult(Table inputTable, string pmmlPath)
{
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(pmmlPath);
string[] predictedCategories = null;
//Predict the value for each record using the PMML Evaluator instance
for (int i = 0; i < inputTable.RowCount; i++)
{
var iris = GetDataObject(inputTable, i);
//Get result
PredictedResult predictedResult = evaluator.GetResult(iris, null);
if (i == 0)
{
//Get the predicted propability fields
predictedCategories = predictedResult.GetPredictedCategories();
//Initialize the output table
InitializeTable(inputTable.RowCount, predictedResult.PredictedField, predictedCategories);
}
//Add predicted value
outputTable[i, 0] = predictedResult.PredictedValue;
for (int j = 1; j <= predictedCategories.Length; j++)
{
outputTable[i, j] = predictedResult.GetPredictedProbability(predictedCategories[j - 1]);
}
}
return(outputTable);
}
public void Predicted_Button(object sender, RoutedEventArgs e)
{
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(viewModel.GetPMMLPath(pmmlPath));
// Input object as dictionary
var bfeed = new
{
duration = duration.Text,
delta = ((ComboBoxItem)delta.SelectedItem).Content.ToString() == "completed" ? 1 : 0,
race = ((ComboBoxItem)race.SelectedItem).Content.ToString() == "black" ? 2 : ((ComboBoxItem)race.SelectedItem).Content.ToString() == "white" ? 1 : 0,
poverty = ((ComboBoxItem)poverty.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
smoke = ((ComboBoxItem)smoke.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
alcohol = ((ComboBoxItem)alcohol.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
agemth = agemth.Text,
ybirth = ybirth.Text,
pc3mth = ((ComboBoxItem)pc3mth.SelectedItem).Content,
yschool = yschool.Text
};
//Get predicted result
PredictedResult predictedResult = evaluator.GetResult(bfeed, null);
viewModel.BfeedCollection = new ObservableCollection <Bfeed>();
viewModel.BfeedCollection.Add(new Bfeed()
{
Observation = string.Empty,
Predicted_Survival = Convert.ToDouble(predictedResult.GetPredictedProbability("survival"))
});
//Change of visibility over input and resultant grid
this.InputGrid.Visibility = Visibility.Collapsed;
this.ResultGrid.Visibility = Visibility.Visible;
}
/// <summary>
/// Gets predicted result of input values as observable collection
/// </summary>
/// <param name="inputTable">current page input values</param>
/// <param name="pageSize">page size</param>
/// <returns>observable collection of predicted results</returns>
private ObservableCollection <BusinessObject> PredictResult(Table inputTable, int pageSize)
{
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(viewModel.GetPMMLPath(pmmlPath));
//Initialize the output table
InitializeTable(inputTable.RowCount);
//Gets the start index of page selected
int startIndex = sfDataPager.PageIndex * sfDataPager.PageSize;
//Predict the value for each record using the PMML Evaluator instance
for (int i = 0; i < inputTable.RowCount; i++)
{
//Get input values as dictionary object
Dictionary <string, object> iris = inputTable.ColumnNames.ToDictionary(column => column, column
=> inputTable[i, column]);
//Get result
PredictedResult predictedResult = evaluator.GetResult(iris, null);
//Add predicted value
outputTable[i, 0] = predictedResult.PredictedValue;
for (int j = 1; j <= predictedResult.GetPredictedCategories().Length; j++)
{
outputTable[i, j] = predictedResult.GetPredictedProbability(predictedResult.GetPredictedCategories()[j - 1]);
}
//Adds predicted species result to the collection for visualization
if (!predictedSpeciesCollection.ContainsKey((startIndex + i + 1).ToString()))
{
iris.Add("predictedSpecies", predictedResult.PredictedValue);
iris.Add("species_Setosa", predictedResult.GetPredictedProbability(predictedResult.GetPredictedCategories()[0]));
iris.Add("species_Versicolor", predictedResult.GetPredictedProbability(predictedResult.GetPredictedCategories()[1]));
iris.Add("species_Virginica", predictedResult.GetPredictedProbability(predictedResult.GetPredictedCategories()[2]));
predictedSpeciesCollection.Add((startIndex + i + 1).ToString(), iris);
}
}
// Merges the selected page inputs and their output values
var result = viewModel.MergeTable(inputTable, outputTable, inputDataTable);
return(result);
}
public void Predicted_Button(object sender, RoutedEventArgs e)
{
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(viewModel.GetPMMLPath(pmmlPath));
// Input object as dictionary
var wine = new
{
Alcohol = alcohol.Text,
Malic = malic.Text,
Ash = ash.Text,
Alcalinity = alkalinity.Text,
Magnesium = magnesium.Text,
Phenols = phenols.Text,
Flavanoids = flavanoids.Text,
Nonflavanoids = nonflavanoids.Text,
Proanthocyanins = proanthocyanins.Text,
Color = color.Text,
Hue = hue.Text,
Dilution = dilution.Text,
Proline = proline.Text
};
//Get predicted result
PredictedResult predictedResult = evaluator.GetResult(wine, null);
viewModel.WineCollection = new ObservableCollection <Wine>();
viewModel.WineCollection.Add(new Wine()
{
Type = string.Empty,
Wine1_probability = Convert.ToDouble(predictedResult.GetPredictedProbability("1")),
Wine2_probability = Convert.ToDouble(predictedResult.GetPredictedProbability("2")),
Wine3_probability = Convert.ToDouble(predictedResult.GetPredictedProbability("3"))
});
//Change of visibility over input and resultant grid
this.InputGrid.Visibility = Visibility.Collapsed;
this.ResultGrid.Visibility = Visibility.Visible;
}
/// <summary>
/// Gets predicted result of input values as observable collection
/// </summary>
/// <param name="inputTable">current page input values</param>
/// <param name="pageSize">page size</param>
/// <returns>observable collection of predicted results</returns>
private ObservableCollection <BusinessObject> PredictResult(Table inputTable, int pageSize)
{
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(viewModel.GetPMMLPath(pmmlPath));
//Initialize the output table
InitializeTable(inputTable.RowCount);
//Gets the start index of page selected
int startIndex = sfDataPager.PageIndex * sfDataPager.PageSize;
//Predict the value for each record using the PMML Evaluator instance
for (int i = 0; i < inputTable.RowCount; i++)
{
//Get input values as dictionary object
Dictionary <string, object> bfeed = inputTable.ColumnNames.ToDictionary(column => column, column
=> inputTable[i, column]);
//Get result
PredictedResult predictedResult = evaluator.GetResult(bfeed, null);
//Add predicted value
outputTable[i, 0] = predictedResult.PredictedValue;
//Add predicted Survival
outputTable[i, 1] = predictedResult.GetPredictedProbability("survival");
//Adds predicted survival time values to the collection for visualization
if (!predictedSurvivalCollection.ContainsKey((startIndex + i + 1).ToString()))
{
bfeed.Add("CumulativeHazard", predictedResult.PredictedValue);
bfeed.Add("Predicted_Survival", predictedResult.GetPredictedProbability("survival"));
predictedSurvivalCollection.Add((startIndex + i + 1).ToString(), bfeed);
}
}
// Merges the selected page inputs and their output values
var result = viewModel.MergeTable(inputTable, outputTable, inputDataTable);
return(result);
}
public void Predicted_Button(object sender, RoutedEventArgs e)
{
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(viewModel.GetPMMLPath(pmmlPath));
// Input object as dictionary
var audit = new
{
Age = age.Text,
Employment = ((ComboBoxItem)EmploymentCombo.SelectedItem).Content,
Education = ((ComboBoxItem)EducationCombo.SelectedItem).Content,
Marital = ((ComboBoxItem)MaritalCombo.SelectedItem).Content,
Occupation = ((ComboBoxItem)OccupationCombo.SelectedItem).Content,
Income = income.Text,
Sex = ((ComboBoxItem)SexCombo.SelectedItem).Content,
Deductions = deductions.Text,
Hours = hours.Text,
Accounts = ((ComboBoxItem)AccountsCombo.SelectedItem).Content,
Adjustment = adjustment.Text,
};
//Get predicted result
PredictedResult predictedResult = evaluator.GetResult(audit, null);
viewModel.AuditCollection = new ObservableCollection <Audit>();
viewModel.AuditCollection.Add(new Audit()
{
Status = string.Empty,
Adjustable_probability = Convert.ToDouble(predictedResult.GetPredictedProbability("0")),
NonAdjustable_probability = Convert.ToDouble(predictedResult.GetPredictedProbability("1")),
});
//Change of visibility over input and resultant grid
this.InputGrid.Visibility = Visibility.Collapsed;
this.ResultGrid.Visibility = Visibility.Visible;
}