public Booster(Parameters parameters, Dataset trainset, Dataset validset = null)
{
var param = parameters.ToString();
var handle = IntPtr.Zero;
PInvokeException.Check(PInvoke.BoosterCreate(trainset.Handle, param, ref handle), nameof(PInvoke.BoosterCreate));
Handle = handle;
if (validset != null)
{
PInvokeException.Check(PInvoke.BoosterAddValidData(handle, validset.Handle), nameof(PInvoke.BoosterAddValidData));
_hasValid = true;
}
BestIteration = -1;
int numEval = this.EvalCounts;
// At most one metric in ML.NET: to do remove this.
if (numEval > 1)
{
throw new Exception($"Expected at most one metric, got {numEval}");
}
else if (numEval == 1)
{
_hasMetric = true;
}
}
public Booster(Parameters parameters, Dataset trainset, Dataset validset = null)
{
if (trainset.CommonParameters != parameters.Common)
throw new Exception("CommonParameters differ from those used to create training set");
if (trainset.DatasetParameters != parameters.Dataset)
throw new Exception("DatasetParameters differ from those used to create training set");
if (validset != null)
{
if (validset.CommonParameters != parameters.Common)
throw new Exception("CommonParameters differ from those used to create validation set");
if (validset.DatasetParameters != parameters.Dataset)
throw new Exception("DatasetParameters differ from those used to create validation set");
}
var param = parameters.ToString();
var handle = IntPtr.Zero;
PInvokeException.Check(PInvoke.BoosterCreate(trainset.Handle, param, ref handle),nameof(PInvoke.BoosterCreate));
Handle = handle;
if (validset != null)
{
PInvokeException.Check(PInvoke.BoosterAddValidData(handle, validset.Handle),nameof(PInvoke.BoosterAddValidData));
_hasValid = true;
}
BestIteration = -1;
int numEval = this.EvalCounts;
// At most one metric in ML.NET: to do remove this.
if (numEval > 1)
throw new Exception($"Expected at most one metric, got {numEval}");
else if (numEval == 1)
_hasMetric = true;
}
