public IDataTable ConvertToNumeric(IDataTableVectoriser vectoriser = null, bool useTargetColumnIndex = true, Stream output = null)
{
var writer = new DataTableWriter(output);
vectoriser = vectoriser ?? GetVectoriser(useTargetColumnIndex);
// add the numeric columns
foreach (var name in vectoriser.ColumnNames)
{
writer.AddColumn(name, ColumnType.Float);
}
// add the classification label column
var classColumnIndex = TargetColumnIndex;
if (useTargetColumnIndex)
{
var classColumn = _column[classColumnIndex];
writer.AddColumn(classColumn.Name, ColumnType.String, true);
}
// vectorise each row
_Iterate((row, i) => {
var rowData = vectoriser.GetInput(row).Data.AsEnumerable().Cast <object>();
if (useTargetColumnIndex)
{
rowData = rowData.Concat(new object[] { row.GetField <string>(classColumnIndex) });
}
writer.AddRow(new DataTableRow(this, rowData.ToArray(), _rowConverter));
return(true);
});
return(writer.GetDataTable());
}
public IDataTable ConvertToNumeric(IDataTableVectoriser vectoriser = null, Stream output = null)
{
var writer = new DataTableWriter(output);
vectoriser = vectoriser ?? GetVectoriser();
foreach (var name in vectoriser.ColumnNames)
{
writer.AddColumn(name, ColumnType.Float);
}
var classColumnIndex = TargetColumnIndex;
var classColumn = _column[classColumnIndex];
writer.AddColumn(classColumn.Name, ColumnType.String, true);
_Iterate(row => {
var data = vectoriser.GetInput(row).AsEnumerable().Cast <object>().Concat(new object[] { row.GetField <string>(classColumnIndex) });
writer.AddRow(data);
return(true);
});
return(writer.GetDataTable());
}
public float[] Encode(IRow row)
{
return(_vectoriser.GetInput(row).Data);
}
Tuple <float[], float[]> _Convert(IRow row)
{
return(Tuple.Create(_vectoriser.GetInput(row), _vectoriser.GetOutput(row)));
}
