/// <summary> /// Predicts the results for given PMML and CSV file and serialize the results in a CSV file /// </summary> 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 tips = new { sex = ((ComboBoxItem)SexCombo.SelectedItem).Content, smoker = ((ComboBoxItem)SmokerCombo.SelectedItem).Content, day = ((ComboBoxItem)DayCombo.SelectedItem).Content, time = ((ComboBoxItem)TimeCombo.SelectedItem).Content, size = size.Text, total_bill = totalbill.Text }; //Get predicted result PredictedResult predictedResult = evaluator.GetResult(tips, null); this.PredictedTip.Text = "Tip Amount : " + "\"" + 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> /// 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); //Predict the value for each record using the PMML Evaluator instance for (int i = 0; i < inputTable.RowCount; i++) { var audit = GetDataObject(inputTable, i); //Get result PredictedResult predictedResult = evaluator.GetResult(audit, null); if (i == 0) { //Initialize the output table InitializeTable(inputTable.RowCount, predictedResult.PredictedField); } //Add predicted value outputTable[i, 0] = predictedResult.PredictedValue; } 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 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; }
public void Tip( string league, int round) { Predictions.Clear(); var sched = Context.LeagueSchedule[league][round]; foreach (var game in sched) { var prediction = new PredictedResult(game); // just uses table position to predict var homeRank = GetRank(game.HomeTeam); var awayRank = GetRank(game.AwayTeam); if (homeRank < awayRank) { prediction.HomeWin = true; prediction.AwayWin = false; } else { prediction.HomeWin = false; prediction.AwayWin = true; } Predictions.Add(prediction); } }
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 ozone = new { Month = month.Text, Day_of_month = dayofmonth.Text, Day_of_week = dayofweek.Text, pressure_height = pressureheight.Text, Wind_speed = windspeed.Text, Humidity = humidity.Text, Temperature_at_Sandburg = temperatureatsandburg.Text, Temperature_at_El_Monte = temperartureatelmonte.Text, Inversion_base_height = inversionbaseheight.Text, Pressure_gradient = pressuregradient.Text, Inversion_base_temperature = inversionbasetemperature.Text, Visibility = visibility.Text }; //Get predicted result PredictedResult predictedResult = evaluator.GetResult(ozone, null); this.PredictedReading.Text = "Ozone Reading : " + "\"" + Math.Round(predictedResult.PredictedDoubleValue, 2).ToString() + "\""; //Change of visibility over input and resultant grid this.InputGrid.Visibility = Windows.UI.Xaml.Visibility.Collapsed; this.ResultGrid.Visibility = Windows.UI.Xaml.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 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; }
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 Dictionary <string, object> glass = new Dictionary <string, object>(); glass.Add("RI", ri.Text); glass.Add("Na", na.Text); glass.Add("Mg", mg.Text); glass.Add("Al", al.Text); glass.Add("Si", si.Text); glass.Add("K", k.Text); glass.Add("Ca", ca.Text); glass.Add("Ba", ba.Text); glass.Add("Fe", fe.Text); //Get predicted result PredictedResult predictedResult = evaluator.GetResult(glass, null); glass.Add("predictedCluster", predictedResult.PredictedValue); this.PredictedPrice.Text = "Predicted Group : \"Cluster" + predictedResult.PredictedValue + "\""; //Binds output result for visualization BindOutputResults(glass); //Change of visibility over input and resultant grid this.InputGrid.Visibility = Visibility.Collapsed; this.ResultGrid.Visibility = Visibility.Visible; }
private void button_Click(object sender, EventArgs e) { PMMLEvaluator evaluator = new PMMLEvaluatorFactory(). GetPMMLEvaluatorInstance(new PMMLDocument(new MemoryStream(Encoding.ASCII.GetBytes(File.ReadAllText("Data/Audit.pmml"))))); //Create and anonymous type for audit record var audit = new { ID = 0, Age = AgeTextValue.Text.Trim() != "" ? AgeTextValue.Text : "20", Employment = EmploymentCollection.SelectedItem, Education = EducationCollection.SelectedItem, Marital = MaritalCollection.SelectedItem, Occupation = OccupationCollection.SelectedItem, Income = IncomeTextValue.Text.Trim() != "" ? IncomeTextValue.Text.ToString() : "20000", Sex = GenderCollection.SelectedItem, Deductions = DeductionTextValue.Text.Trim() != "" ? DeductionTextValue.Text.ToString() : "10000", Hours = HoursTextValue.Text.Trim() != "" ? HoursTextValue.Text.ToString() : "12", Accounts = AccountsCollection.SelectedItem, Adjustment = 0 }; //Get predicted result PredictedResult predictedResult = evaluator.GetResult(audit, null); //Get predicted category 0 or 1 string auditPredicted = (predictedResult.PredictedValue != null) ? predictedResult.PredictedValue.ToString() : "-"; // Display result based on predicted category thumb.Image = auditPredicted == "0" ? Image.FromFile("Images/thumb_yes.png") : Image.FromFile("Images/thumb_no.png"); AuditPredicted.Text = auditPredicted == "0" ? "YES!" : "NO!"; PredictedText.Text = auditPredicted == "0" ? "Your audit risk is low." : "Your audit risk is high."; }
/// <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); }
private void PredictMethod(object param) { PMMLEvaluator evaluator = new PMMLEvaluatorFactory(). GetPMMLEvaluatorInstance("../../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() : "-"; //Display result based on predicted category ImagePath = predicted == "0" ? "/Images/thumb_yes.png" : "/Images/thumb_no.png"; AuditPredicted = predicted == "0" ? "YES!" : "NO!"; PredictedText = predicted == "0" ? "Your audit risk is low." : "Your audit risk is high."; }
/// <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 glass = GetDataObject(inputTable, i); //Get result PredictedResult predictedResult = evaluator.GetResult(glass, 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); }
private void PredictMethod(object param) { PMMLEvaluator evaluator = new PMMLEvaluatorFactory(). GetPMMLEvaluatorInstance(new PMMLDocument(new MemoryStream(Encoding.ASCII.GetBytes(File.ReadAllText("Assets/AuditShowcase/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() : "-"; //Display result based on predicted category ImagePath = predicted == "0" ? "/syncfusion.auditshowcase.wpf;component/Assets/AuditShowcase/thumb_yes.png" : "/syncfusion.auditshowcase.wpf;component/Assets/AuditShowcase/thumb_no.png"; AuditPredicted = predicted == "0" ? "YES!" : "NO!"; PredictedText = predicted == "0" ? "Your audit risk is low." : "Your audit risk is high."; }
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; }
/// <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); //Predict the recommendations, exclusiveRecommendations and ruleAssociations for each transactions using the PMML Evaluator instance for (int i = 0; i < inputTable.RowCount; i++) { // Groups list of items for each 'transaction ID' as collection List <string> input = inputTable[i, 1].ToString().Replace("{", "").Replace("}", "").Split(new char[] { ',' }).ToList(); //Get result PredictedResult predictedResult = evaluator.GetResult(input, null); //Get recommended items with their confidences and here it is added to collection for visualization if (!recommendedItemCollection.ContainsKey(inputTable[i, 0].ToString())) { recommendedItemCollection.Add(inputTable[i, 0].ToString(), ((AssociationModelResult)predictedResult).GetConfidences(RecommendationType.Recommendation)); } // Binds recommended items array in the following format to display it in the grid outputTable[i, 0] = "[" + string.Join(",", predictedResult.GetRecommendations()) + "]"; outputTable[i, 1] = "[" + string.Join(",", predictedResult.GetExclusiveRecommendations()) + "]"; outputTable[i, 2] = "[" + string.Join(",", predictedResult.GetRuleAssociations()) + "]"; } // 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)); }
/// <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 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; }
public PredictedResult Tip( Game g) { var result = new PredictedResult(g); var homeOff = Ratings[g.HomeTeam].Offence; var homeDef = Ratings[g.HomeTeam].Defence; var awayOff = Ratings[g.AwayTeam].Offence; var awayDef = Ratings[g.AwayTeam].Defence; var homeScore = AverageScore + ((homeOff + awayDef) / 2); var awayScore = AverageScore + ((awayOff + homeDef) / 2); result.HomeScore = MaxMin((int)homeScore); result.AwayScore = MaxMin((int)awayScore); return(result); }
/// <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); }
/// <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); }
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); }
/// <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 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; }
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 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 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; }