/// <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);
}
/// <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> imports = inputTable.ColumnNames.ToDictionary(column => column, column
=> inputTable[i, column]);
//Get result
PredictedResult predictedResult = evaluator.GetResult(imports, null);
//Adds predicted ozone reading values to the collection for visualization
if (!predictedPriceDetails.ContainsKey((startIndex + i + 1).ToString()))
{
imports.Add("predictedPrice", predictedResult.PredictedDoubleValue);
predictedPriceDetails.Add((startIndex + i + 1).ToString(), imports);
}
//Add predicted value
outputTable[i, 0] = predictedResult.PredictedValue;
}
// Merges the selected page inputs and their output values
var result = viewModel.MergeTable(inputTable, outputTable, inputDataTable);
return(result);
}
public string PredictMethod()
{
//image path
string imagePath = "ms-appx:///PredictiveAnalytics/ShowCase/AuditDemo/Images";
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(new ViewModel().
GetPMMLPath("ms-appx:///PredictiveAnalytics/ShowCase/AuditDemo/Data/Audit.pmml"));
//Create and anonymous type for audit record
var audit = new
{
ID = 0,
Age = AgeTextValue,
Employment = EmploymentSelectedValue,
Education = EducationSelectedValue,
Marital = MaritalSelectedValue,
Occupation = OccupationSelectedValue,
Income = IncomeTextValue,
Sex = GenderSelectedValue,
Deductions = DeductionTextValue,
Hours = HoursTextValue,
Accounts = AccountsSelectedValue,
Adjustment = 0
};
//Get predicted result
PredictedResult predictedResult = evaluator.GetResult(audit, null);
//Get predicted category 0 or 1
string predicted = (predictedResult.PredictedValue != null) ? predictedResult.PredictedValue.ToString() : "-";
if (predicted.Equals("0"))
{
Image img = new Image();
img.Source = new BitmapImage(new Uri(imagePath + "/thumb_yes.png"));
ImagePath = img.Source;
}
else
{
Image img = new Image();
img.Source = new BitmapImage(new Uri(imagePath + "/thumb_no.png"));
ImagePath = img.Source;
}
AuditPredicted = predicted == "0" ? "YES!" : "NO!";
PredictedText = predicted == "0" ? "Your audit risk is low." : "Your audit risk is high.";
return(PredictedText);
}
protected void Predict_Click(object sender, EventArgs e)
{
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(Server.MapPath("~/App_Data/Audit.pmml"));
string age = Age.Value.ToString();
string income = Income.Value.ToString();
string deduction = Deduction.Value.ToString();
string hours = Hours.Value.ToString();
age = string.IsNullOrEmpty(age) ? "0" : age;
income = string.IsNullOrEmpty(income) ? "0" : income;
deduction = string.IsNullOrEmpty(deduction) ? "0" : deduction;
hours = string.IsNullOrEmpty(hours) ? "0" : hours;
var audit = new
{
ID = 0,
Age = Convert.ToInt32(age),
Employment = EmploymentCollection.Value,
Education = EducationCollection.Value,
Marital = MaritalCollection.Value,
Occupation = OccupationCollection.Value,
Income = Convert.ToInt32(income),
Sex = GenderCollection.Value,
Deductions = Convert.ToInt32(deduction),
Hours = Convert.ToInt32(hours),
Accounts = AccountsCollection.Value,
Adjustment = 0
};
PredictedResult predictedResult = evaluator.GetResult(audit, null);
string auditPredictedValue = (predictedResult.PredictedValue != null) ? predictedResult.PredictedValue.ToString() : "-";
imagePath.Visible = true;
if (auditPredictedValue == "0")
{
imagePath.ImageUrl = "../Content/images/thumb_yes.png";
option.Text = "YES!";
text.Text = "Your audit risk is low.";
}
else
{
imagePath.ImageUrl = "../Content/images/thumb_no.png";
option.Text = "NO!";
text.Text = "Your audit risk is high.";
}
}
public ActionResult PredictiveAnalyticsFeatures(string PetalLength, string PetalWidth, string SepalLength, string SepalWidth)
{
string pmmlFilePath = Server.MapPath("~/App_Data/IrisTree.pmml");
PMMLEvaluator pmmlEvaluator = new PMMLEvaluatorFactory().GetPMMLEvaluatorInstance(pmmlFilePath);
var anonymousType = new
{
SepalLength = SepalLength,
SepalWidth = SepalWidth,
PetalLength = PetalLength,
PetalWidth = PetalWidth,
};
PredictedResult predictedResult = pmmlEvaluator.GetResult(anonymousType, null);
var result = predictedResult.PredictedValue;
ViewBag.value = result;
return(Content(ViewBag.value));
}
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 imports = new
{
symboling = symboling.Text,
normalizedLosses = normalizedlosses.Text,
make = ((ComboBoxItem)MakeCombo.SelectedItem).Content,
fuelType = ((ComboBoxItem)FuelTypeCombo.SelectedItem).Content,
aspiration = ((ComboBoxItem)AspirationCombo.SelectedItem).Content,
numOfDoors = ((ComboBoxItem)DoorsCombo.SelectedItem).Content,
bodyStyle = ((ComboBoxItem)BodyStyleCombo.SelectedItem).Content,
driveWheels = ((ComboBoxItem)DriveWheelsCombo.SelectedItem).Content,
engineLocation = ((ComboBoxItem)EngineLocationCombo.SelectedItem).Content,
wheelBase = wheelbase.Text,
length = length.Text,
width = width.Text,
height = height.Text,
curbWeight = curbweight.Text,
engineType = ((ComboBoxItem)EngineTypeCombo.SelectedItem).Content,
numOfCylinders = ((ComboBoxItem)CylinderCombo.SelectedItem).Content,
engineSize = enginesize.Text,
fuelSystem = ((ComboBoxItem)FuelSystemCombo.SelectedItem).Content,
bore = bore.Text,
stroke = stroke.Text,
compressionRatio = compression.Text,
horsepower = horsepower.Text,
peakRpm = peakrpm.Text,
cityMpg = citympg.Text,
highwayMpg = highwaympg.Text,
};
//Get predicted result
PredictedResult predictedResult = evaluator.GetResult(imports, null);
this.PredictedPrice.Text = " Vehicle's Price : " + "\"" + Math.Round(predictedResult.PredictedDoubleValue, 2).ToString() + "\"";
//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);
}
/// <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)
{
string[] recommendations = null;
string[] exclusiveRecommendations = null;
string[] ruleAssociations = null;
List <string> input = null;
int index = 0;
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(pmmlPath);
for (int i = 0; i < inputTable.ColumnNames.Length; i++)
{
if (inputTable.ColumnNames[i].ToLower() == "items")
{
index = i;
}
}
//Predict the recommendations, exclusiveRecommendations and ruleAssociations for each transactions using the PMML Evaluator instance
for (int i = 0; i < inputTable.RowCount; i++)
{
input = inputTable[i, index].ToString().Replace("{", "").Replace("}", "").Split(new char[] { ',' }).ToList();
//Get result
PredictedResult predictedResult = evaluator.GetResult(input, null);
recommendations = predictedResult.GetRecommendations();
exclusiveRecommendations = predictedResult.GetExclusiveRecommendations();
ruleAssociations = predictedResult.GetRuleAssociations();
if (i == 0)
{
InitializeTable(inputTable.RowCount);
}
outputTable[i, 0] = "[" + string.Join(",", recommendations) + "]";
outputTable[i, 1] = "[" + string.Join(",", exclusiveRecommendations) + "]";
outputTable[i, 2] = "[" + string.Join(",", ruleAssociations) + "]";
}
return(outputTable);
}
/// <summary>
/// Predicts the results for given PMML and CSV file and serialize the results in a CSV file
/// </summary>
public Syncfusion.PMML.Table PredictResult(string[] input, string pmmlPath)
{
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(pmmlPath);
string[] predictedCategories = null;
int i = 0;
foreach (string s in input)
{
string[] predictedandInput = s.Split(',');
string[] inputField = predictedandInput[1].Split(' ');
var record = new
{
field_0 = inputField[0],
field_1 = inputField[1],
field_2 = inputField[2],
field_3 = inputField[3],
field_4 = inputField[4],
field_5 = inputField[5],
field_6 = inputField[6],
field_7 = inputField[7]
};
PredictedResult predictedResult = evaluator.GetResult(record, null);
if (i == 0)
{
//Get the predicted propability fields
predictedCategories = predictedResult.GetPredictedCategories();
//Initialize the output table
InitializeTable(input.Length, predictedCategories);
}
//Add predicted value
outputTable[i, 0] = predictedResult.PredictedDoubleValue;
i++;
}
return(outputTable);
}
static void Main(string[] args)
{
Console.WriteLine("Starting PMML demo...");
var predictors = new
{
predictor_1 = 0.3,
predictor_2 = 0.2,
predictor_3 = 3.2,
predictor_4 = 1.2
};
string fileName = "model.pmml";
string path = Path.Combine(Environment.CurrentDirectory, fileName);
Console.WriteLine("File path " + path);
PMMLEvaluator PMMLEvaluator = new PMMLEvaluatorFactory().GetPMMLEvaluatorInstance(path);
PredictedResult predictedResult = PMMLEvaluator.GetResult(predictors, null);
}
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 PartialViewResult Index(int Age, string Income, string Deduction, int Hours, string Accounts, string Employment, string Education, string Sex, string Marital, string Occupation)
{
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(Server.MapPath("~/App_Data/Audit.pmml"));
var audit = new
{
Age = Age,
Employment = Employment,
Education = Education,
Marital = Marital,
Occupation = Occupation,
Income = Income,
Sex = Sex,
Deductions = Deduction,
Hours = Hours,
Accounts = Accounts,
};
PredictedResult predictedResult = evaluator.GetResult(audit, null);
var Adjusted = (predictedResult.PredictedValue != null) ? predictedResult.PredictedValue.ToString() : "-";
if (Adjusted == "0")
{
ViewBag.Adjusted = Url.Content("~/Content/images/thumb_yes.png");
ViewBag.Result = "YES!";
ViewBag.Text = "Your audit risk is low.";
}
else
{
ViewBag.Adjusted = Url.Content("~/Content/images/thumb_no.png");
ViewBag.Result = "NO!";
ViewBag.Text = "Your audit risk is high.";
}
return(PartialView("AuditResult"));
}
public Table PredictResult(string[] input, string pmmlPath)
{
//Get PMML Evaluator instance
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(pmmlPath);
string[] predictedCategories = null;
int i = 0;
foreach (string s in input)
{
string[] words = s.Split(' ');
var record = new
{
field_0 = words[0],
field_1 = words[1],
field_2 = words[2]
};
PredictedResult predictedResult = evaluator.GetResult(record, null);
if (i == 0)
{
//Get the predicted propability fields
predictedCategories = predictedResult.GetPredictedCategories();
//Initialize the output table
InitializeTable(input.Length, predictedCategories);
}
//Add predicted value
outputTable[i, 0] = predictedResult.PredictedValue;
i++;
}
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 cars = new
{
Mileage = mileage.Text,
Cylinder = ((ComboBoxItem)cylinder.SelectedItem).Content,
Doors = ((ComboBoxItem)doors.SelectedItem).Content,
Cruise = ((ComboBoxItem)cruise.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
Sound = ((ComboBoxItem)sound.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
Leather = ((ComboBoxItem)leather.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
Buick = ((ComboBoxItem)buick.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
Cadillac = ((ComboBoxItem)cadillac.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
Chevy = ((ComboBoxItem)chevy.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
Pontiac = ((ComboBoxItem)pontiac.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
Saab = ((ComboBoxItem)saab.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
Saturn = ((ComboBoxItem)saturn.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
convertible = ((ComboBoxItem)convertible.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
coupe = ((ComboBoxItem)coupe.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
hatchback = ((ComboBoxItem)hatchback.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
sedan = ((ComboBoxItem)sedan.SelectedItem).Content.ToString() == "yes" ? 1 : 0,
wagon = ((ComboBoxItem)wagon.SelectedItem).Content.ToString() == "yes" ? 1 : 0
};
//Get predicted result
PredictedResult predictedResult = evaluator.GetResult(cars, null);
this.PredictedPrice.Text = "Car's Price : " + "\"" + Math.Round(predictedResult.PredictedDoubleValue, 2).ToString() + "\"";
//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 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;
}
public ActionResult Analysis(string city, string title, string familysize)
{
string pmmlFilePath = Server.MapPath("~/App_Data/train.pmml");
PMMLEvaluator pmmlEvaluator = new PMMLEvaluatorFactory().GetPMMLEvaluatorInstance(pmmlFilePath);
var anonymousType = new
{
city = city,
title = title,
familysize = familysize
};
PredictedResult predictedResult = pmmlEvaluator.GetResult(anonymousType, null);
var result = predictedResult.PredictedValue;
ViewBag.value = result;
if (ViewBag.value == "0")
{
ViewBag.result = "He will not buy";
}
else
{
ViewBag.result = "He will buy";
}
return(Content(ViewBag.result));
}
private void Transactions_SelectionChanged(object sender, SelectionChangedEventArgs e)
{
Dictionary <string, decimal> recommendedItems = null;
//Initializes the collection of recommended items for visualization
viewModel.RecommendedGroceries = new ObservableCollection <RecommendedGroceries>();
if ((sender as ComboBox).SelectedIndex != -1)
{
//Mobile visualization
if (Windows.Foundation.Metadata.ApiInformation.IsTypePresent("Windows.Phone.UI.Input.HardwareButtons"))
{
PMMLEvaluator evaluator = new PMMLEvaluatorFactory().
GetPMMLEvaluatorInstance(viewModel.GetPMMLPath(pmmlPath));
switch (((ComboBoxItem)(sender as ComboBox).SelectedValue).Content.ToString())
{
case "1":
viewModel.PurchasedItems = "citrus fruit,semi-finished bread";
break;
case "2":
viewModel.PurchasedItems = "tropical fruit,yogurt,coffee";
break;
case "3":
viewModel.PurchasedItems = "pip fruit,yogurt,cream cheese";
break;
case "4":
viewModel.PurchasedItems = "other vegetables,whole milk";
break;
case "5":
viewModel.PurchasedItems = "butter,sugar,fruit/vegetable juice";
break;
}
// Groups list of items for each 'transaction ID' as collection
List <string> input = viewModel.PurchasedItems.Split(',').ToList();
//Get result
PredictedResult predictedResult = evaluator.GetResult(input, null);
//Adds Recommended items
recommendedItems = ((AssociationModelResult)predictedResult).GetConfidences(RecommendationType.Recommendation);
}
else
{
//Gets the start index of page selected
int startIndex = sfDataPager.PageIndex * sfDataPager.PageSize;
//Adds purchased items for selected transaction
viewModel.PurchasedItems = inputDataTable[(startIndex + Transactions.SelectedIndex), 1].ToString().Replace("{", "").
Replace("}", "").Replace(",", ", ");
//Adds Recommended items as collection
recommendedItems = (Dictionary <string, decimal>)recommendedItemCollection[(startIndex +
Transactions.SelectedIndex + 1).ToString()];
}
foreach (var item in recommendedItems)
{
if (!viewModel.PurchasedItems.Contains(item.Key))
{
//Adds recommended items with its confidence value as item source for visualization
viewModel.RecommendedGroceries.Add(new RecommendedGroceries()
{
Item = item.Key,
Confidence = item.Value
});
}
}
}
}
