private static string[] ColumnNames(bool withLabel, ModelValue prediction)
{
var columns = new List <string>();
var data = new ModelDataSet();
for (int i = 0; i < data.Features(); i++)
{
columns.Add(data.Name(i));
}
if (withLabel)
{
switch (prediction)
{
case ModelValue.Action: columns.Add("Action"); break;
case ModelValue.Angle: columns.Add("FaceAngle"); break;
case ModelValue.XY: columns.Add("MoveAngle"); break;
default: throw new Exception("Unknown value for prediction : " + prediction);
}
}
return(columns.ToArray());
}
public override float Predict(ModelDataSet input)
{
if (TrainedModel == null)
{
throw new Exception("Must initialize the model before calling");
}
lock (TrainedModel)
{
// cache for reuse
if (PredictInput == null)
{
PredictInput = new float[input.Features()];
}
for (int i = 0; i < PredictInput.Length; i++)
{
PredictInput[i] = input.Feature(i);
}
using (var arr = InputArray.Create <float>(PredictInput))
{
return(TrainedModel.Predict(arr));
}
}
}