/// <summary>
/// Initialize the outputTable
/// </summary>
/// <param name="rowCount">rowCount of output table</param>
/// <param name="predictedfield">predictedfield name</param>
/// <param name="predictedCategories">probableFields</param>
private void InitializeTable(int rowCount, string[] predictedCategories)
{
//Create instance to hold evaluated results
outputTable = new Syncfusion.PMML.Table(rowCount, predictedCategories.Length + 1);
//Add predicted column names
outputTable.ColumnNames[0] = "Predicted";
}
private void button1_Click(object sender, RoutedEventArgs e)
{
var value = 0;
string pmmlPath = "../../Model/kmeans_data.pmml";
string inputPath = "../../Model/kmeans_data.txt";
string[] lines = System.IO.File.ReadAllLines(inputPath);
outputTable = PredictResult(lines, pmmlPath);
DataTable inputDataTable = new DataTable();
string[] words = lines[0].Split(' ');
value = words.Length;
for (int i = 0; i < value; i++)
{
inputDataTable.Columns.Add("field_" + i);
}
foreach (var item in lines)
{
words = item.Split(' ');
inputDataTable.Rows.Add(words);
}
var MergedDataTable = MergeTable(inputDataTable, outputTable);
SfDataGrid.ItemsSource = MergedDataTable;
for (int i = 0; i < MergedDataTable.Columns.Count; i++)
{
if (i >= value)
{
SfDataGrid.Columns[i].CellStyle = System.Windows.Application.Current.Resources["predictedColumnColor"] as Style;
}
}
}
/// <summary>
/// Method to load Samples
/// </summary>
/// <param name="sample">Sample values</param>
public void LoadGeneralRegressionAuditSample(Sample sample, DataManager dataManager)
{
AuditLogitClassification.Program audit = new AuditLogitClassification.Program();
var path = sample.GetParentDirectoryPath(Server.MapPath("~"));
string samplePath = string.Format("{0}{1}\\{2}", path, sample.SamplePath, "Model\\");
string outputPath = samplePath + "PredictedOutput.html";
string pmmlPath = string.Format("{0}{1}.pmml", samplePath, "Audit");
string rScriptPath = string.Format("{0}{1}.R", samplePath, "Audit");
string inputPath = samplePath + "Audit.csv";
Table inputTable = new Syncfusion.PMML.Table(inputPath, true, ',');
Table selectedPageInputTable = sample.PagingMethod(inputTable, dataManager, dataManager != null ? dataManager.Skip : 0);
Table outputTable = audit.PredictResult(selectedPageInputTable, pmmlPath);
ViewBag.output = sample.serializeTable(inputTable, outputTable, dataManager != null ? dataManager.Skip : 0);
Dictionary <string, List <string> > columnCollection = sample.GetColumnNames(inputTable, outputTable);
ViewBag.InputColumns = columnCollection["inputColumns"];
ViewBag.OutputColumns = columnCollection["outputColumns"];
ViewBag.InputNumericColumns = columnCollection["inputNumericColumns"];
ViewBag.OutputNumericColumns = columnCollection["outputNumericColumns"];
if (System.IO.File.Exists(rScriptPath))
{
ViewBag.RScript = System.IO.File.ReadAllText(rScriptPath);
}
ViewBag.PMML = System.IO.File.ReadAllText(pmmlPath);
}
/// <summary>
/// Serialize the values in a list
/// </summary>
/// <param name="inputTable">input table values</param>
/// <param name="outputTable">output table values</param>
public void serializeTable(Syncfusion.PMML.Table inputTable, Syncfusion.PMML.Table outputTable)
{
List <AuditLogitClassification> datasource = new List <AuditLogitClassification>();
for (int i = 0; i < inputTable.RowCount; i++)
{
AuditLogitClassification auditLogit = new AuditLogitClassification();
auditLogit.ID = inputTable[i, 0];
auditLogit.Age = inputTable[i, 1];
auditLogit.Employment = inputTable[i, 2];
auditLogit.Education = inputTable[i, 3];
auditLogit.Marital = inputTable[i, 4];
auditLogit.Occupation = inputTable[i, 5];
auditLogit.Income = inputTable[i, 6];
auditLogit.Sex = inputTable[i, 7];
auditLogit.Deductions = inputTable[i, 8];
auditLogit.Hours = inputTable[i, 9];
auditLogit.Accounts = inputTable[i, 10];
auditLogit.Adjustment = inputTable[i, 11];
auditLogit.Adjusted = inputTable[i, 12];
auditLogit.Predicted_Adjusted = outputTable[i, 0];
auditLogit.AuditLowriskProbability = outputTable[i, 1];
auditLogit.AuditHighriskProbability = outputTable[i, 2];
//Adds audit object to grid's datasource
datasource.Add(auditLogit);
}
ViewBag.datasource = datasource;
}
/// <summary>
/// Initialize the outputTable
/// </summary>
/// <param name="rowCount">rowCount of output table</param>
/// <param name="predictedfield">predictedfield name</param>
/// <param name="predictedCategories">probableFields</param>
private void InitializeTable(int rowCount, string predictedfield, string[] predictedCategories)
{
//Create instance to hold evaluated results
outputTable = new Table(rowCount, predictedCategories.Length + 1);
//Add predicted column names
outputTable.ColumnNames[0] = "Predicted_" + predictedfield;
outputTable.ColumnNames[1] = "AuditLowriskProbability";
outputTable.ColumnNames[2] = "AuditHighriskProbability";
}
private DataTable MergeTable(DataTable inputDataTable, Syncfusion.PMML.Table outputTable)
{
var lenth = 0;
string pmmlPath = "../../Model/lpsa.pmml";
string inputPath = "../../Model/lpsa.data";
string[] lines = System.IO.File.ReadAllLines(inputPath);
outputTable = PredictResult(lines, pmmlPath);
string[] inputValues = lines[0].Split(' ');
string[] fieldAndTarget = inputValues[0].Split(',');
lenth = inputValues.Length;
for (int i = 0; i < lenth; i++)
{
if (i == 0)
{
inputDataTable.Columns.Add("target");
}
inputDataTable.Columns.Add("field_" + i);
}
foreach (var item in lines)
{
fieldAndTarget = item.Split(',');
var inputList = new List <string>();
inputList.Add(fieldAndTarget[0]);
inputValues = fieldAndTarget[1].Split(' ');
foreach (var word in inputValues)
{
inputList.Add(word);
}
inputValues = inputList.ToArray <string>();
lenth = inputList.Count;
inputDataTable.Rows.Add(inputValues);
}
var columnEnumarator = outputTable.ColumnNames.GetEnumerator();
while (columnEnumarator.MoveNext())
{
var column = new DataColumn()
{
ColumnName = columnEnumarator.Current.ToString()
};
inputDataTable.Columns.Add(column);
}
for (int i = 0; i < inputDataTable.Rows.Count; i++)
{
for (int j = 0; j < outputTable.ColumnNames.Length; j++)
{
inputDataTable.Rows[i].SetField(outputTable.ColumnNames[j], outputTable[i, j]);
}
}
return(inputDataTable);
}
/// <summary>
/// Method to load Samples
/// </summary>
/// <param name="sample">Sample values</param>
public void LoadSample()
{
samplePath = _hostingEnvironment.WebRootPath + @"/PredictiveAnalytics/";
inputPath = samplePath + "Audit.csv";
pmmlPath = string.Format("{0}{1}.pmml", samplePath, "Audit");
Stream inputStream = new FileStream(inputPath, FileMode.Open, FileAccess.Read);
inputTable = new Syncfusion.PMML.Table(inputStream, true, ',');
outputTable = PredictResult(inputTable, pmmlPath);
serializeTable(inputTable, outputTable);
}
private void button1_Click(object sender, RoutedEventArgs e)
{
var lenth = 0;
string pmmlPath = "../../Model/lpsa.pmml";
string inputPath = "../../Model/lpsa.data";
string[] lines = System.IO.File.ReadAllLines(inputPath);
outputTable = PredictResult(lines, pmmlPath);
DataTable inputDataTable = new DataTable();
string[] inputValues = lines[0].Split(' ');
string[] fieldAndTarget = inputValues[0].Split(',');
lenth = inputValues.Length;
for (int i = 0; i < lenth; i++)
{
if (i == 0)
{
inputDataTable.Columns.Add("target");
}
inputDataTable.Columns.Add("field_" + i);
}
foreach (var item in lines)
{
fieldAndTarget = item.Split(',');
var inputList = new List <string>();
inputList.Add(fieldAndTarget[0]);
inputValues = fieldAndTarget[1].Split(' ');
foreach (var word in inputValues)
{
inputList.Add(word);
}
inputValues = inputList.ToArray <string>();
lenth = inputList.Count;
inputDataTable.Rows.Add(inputValues);
}
var MergedDataTable = MergeTable(inputDataTable, outputTable);
SfDataGrid.ItemsSource = MergedDataTable;
for (int i = 0; i < MergedDataTable.Columns.Count; i++)
{
if (i >= lenth)
{
SfDataGrid.Columns[i].CellStyle = System.Windows.Application.Current.Resources["predictedColumnColor"] as Style;
}
}
}
private DataTable MergeTable(DataTable inputDataTable, Syncfusion.PMML.Table outputTable)
{
var value = 0;
string pmmlPath = "../../Model/kmeans_data.pmml";
string inputPath = "../../Model/kmeans_data.txt";
string[] lines = System.IO.File.ReadAllLines(inputPath);
outputTable = PredictResult(lines, pmmlPath);
string[] words = lines[0].Split(' ');
value = words.Length;
for (int i = 0; i < value; i++)
{
inputDataTable.Columns.Add("field_" + i);
}
foreach (var item in lines)
{
words = item.Split(' ');
inputDataTable.Rows.Add(words);
}
var columnEnumarator = outputTable.ColumnNames.GetEnumerator();
while (columnEnumarator.MoveNext())
{
var column = new DataColumn()
{
ColumnName = columnEnumarator.Current.ToString()
};
inputDataTable.Columns.Add(column);
}
for (int i = 0; i < inputDataTable.Rows.Count; i++)
{
for (int j = 0; j < outputTable.ColumnNames.Length; j++)
{
inputDataTable.Rows[i].SetField(outputTable.ColumnNames[j], outputTable[i, j]);
}
}
return(inputDataTable);
}
private DataTable MergeTable(DataTable inputDataTable, Syncfusion.PMML.Table outputTable)
{
var columnEnumarator = outputTable.ColumnNames.GetEnumerator();
while (columnEnumarator.MoveNext())
{
var column = new DataColumn()
{
ColumnName = columnEnumarator.Current.ToString()
};
inputDataTable.Columns.Add(column);
}
for (int i = 0; i < inputDataTable.Rows.Count; i++)
{
for (int j = 0; j < outputTable.ColumnNames.Length; j++)
{
inputDataTable.Rows[i].SetField(outputTable.ColumnNames[j], outputTable[i, j]);
}
}
return(inputDataTable);
}