/// <summary>
/// Evaluates the model on the single input.
/// <seealso cref="EvaluateSingle(float[], string[])"/>
/// </summary>
/// <param name="floatFeatures">Array of float features</param>
/// <param name="catFeatures">Array of categorical features</param>
/// <returns>Array storing model prediction for the input</returns>
public double[] EvaluateSingle(float[] floatFeatures, string[] catFeatures)
{
uint resultSize = GetDimensionsCount(ModelContainer.ModelHandler);
double[] results = new double[resultSize];
bool res = CatBoostModelEvaluator.CalcModelPredictionSingle(
ModelContainer.ModelHandler,
floatFeatures, (uint)floatFeatures.Length,
catFeatures, (uint)catFeatures.Length,
results, resultSize
);
if (res)
{
return(results);
}
else
{
string msg = "";
throw new CatBoostException(
"An error has occurred in the CalcModelPredictionSingle() method in catboostmodel library.\n" +
$"Returned error message: {msg}"
);
}
}
/// <summary>
/// Evaluates the model on the input batch.
/// <seealso cref="EvaluateSingle(float[], string[])"/>
/// </summary>
/// <param name="floatFeatures">
/// 2D array of float features.
/// Should have the same <c>.GetLength(0)</c> as <paramref name="catFeatures"/>
/// </param>
/// <param name="catFeatures">
/// 2D array of categorical features encoded as strings.
/// Should have the same <c>.GetLength(0)</c> as <paramref name="floatFeatures"/>
/// </param>
/// <returns>2D array with model predictions for all samples in the batch</returns>
public double[,] EvaluateBatch(float[,] floatFeatures, string[,] catFeatures)
{
if (floatFeatures.GetLength(0) != catFeatures.GetLength(0))
{
if (floatFeatures.GetLength(0) > 0 && catFeatures.GetLength(0) > 0)
{
throw new CatBoostException("Inconsistent EvaluateBatch arguments:" +
$"got {floatFeatures.GetLength(0)} samples for float features " +
$"but {catFeatures.GetLength(0)} samples for cat features");
}
}
uint docs = (uint)Math.Max(floatFeatures.GetLength(0), catFeatures.GetLength(0));
uint dim = GetDimensionsCount(ModelContainer.ModelHandler);
IntPtr floatFeaturePtr = PointerTools.AllocateToPtr(floatFeatures);
IntPtr catFeaturePtr = PointerTools.AllocateToPtr(catFeatures);
try
{
uint resultSize = dim * docs;
double[] results = new double[resultSize];
bool res = CatBoostModelEvaluator.CalcModelPrediction(
ModelContainer.ModelHandler,
docs,
floatFeaturePtr, (uint)floatFeatures.GetLength(1),
catFeaturePtr, (uint)catFeatures.GetLength(1),
results, resultSize
);
if (res)
{
double[,] resultMatrix = new double[docs, dim];
for (int doc = 0; doc < docs; ++doc)
{
for (int d = 0; d < dim; ++d)
{
resultMatrix[doc, d] = results[dim * doc + d];
}
}
return(resultMatrix);
}
else
{
string msg = "";
throw new CatBoostException(
"An error has occurred in the CalcModelPredictionSingle() method in catboostmodel library.\n" +
$"Returned error message: {msg}"
);
}
}
finally
{
// TODO Deallocate
}
}
/// <summary>
/// Model constructor
/// </summary>
/// <param name="modelFilePath">Path to the model file</param>
/// <param name="targetFeature">Name of the target feature</param>
public CatBoostModel(string modelFilePath, string targetFeature)
{
Evaluator = new CatBoostModelEvaluator(modelFilePath);
TargetFeature = targetFeature;
}
