/// <summary>
/// Analyze the file.
/// </summary>
private void AnalyzeFile()
{
ScriptProperties prop = _analyst.Script.Properties;
// get filenames, headers & format
String sourceID = prop.GetPropertyString(
ScriptProperties.HeaderDatasourceRawFile);
FileInfo sourceFile = _analyst.Script.ResolveFilename(sourceID);
CSVFormat format = _analyst.Script.DetermineFormat();
bool headers = _analyst.Script.ExpectInputHeaders(sourceID);
// read the file
_rowCount = 0;
_missingCount = 0;
var csv = new ReadCSV(sourceFile.ToString(), headers, format);
while (csv.Next())
{
_rowCount++;
if (csv.HasMissing())
{
_missingCount++;
}
}
csv.Close();
}
/**
* Obtain the training set.
* @return The training set.
*/
private IMLDataSet ObtainTrainingSet()
{
ScriptProperties prop = EncogAnalyst.Script.Properties;
String trainingID = prop.GetPropertyString(
ScriptProperties.MlConfigTrainingFile);
FileInfo trainingFile = EncogAnalyst.Script.ResolveFilename(trainingID);
IMLDataSet trainingSet = EncogUtility.LoadEGB2Memory(trainingFile);
return(trainingSet);
}
/**
* Obtain the ML method.
* @return The method.
*/
public IMLMethod ObtainMethod()
{
ScriptProperties prop = EncogAnalyst.Script.Properties;
String resourceID = prop.GetPropertyString(
ScriptProperties.MlConfigMachineLearningFile);
FileInfo resourceFile = EncogAnalyst.Script.ResolveFilename(resourceID);
var method = (IMLMethod)EncogDirectoryPersistence
.LoadObject(resourceFile);
if (!(method is IMLMethod))
{
throw new AnalystError(
"The object to be trained must be an instance of MLMethod. "
+ method.GetType().Name);
}
return(method);
}