// The data are preprocessed (quantized) to avoid sorting
public BoostTree(LabelFeatureDataCoded labelFeatureDataCoded, LabelFeatureData subModelScore,
Model subModel, BoostTreeLoss boostTreeLoss,
string saveTreeBinFile, string saveTreeTextFile)
{
this.labelFeatureDataCoded = labelFeatureDataCoded;
this.subModelScore = subModelScore;
UnpackData();
this.subModel = subModel;
this.boostTreeLoss = boostTreeLoss;
this.featureNames = labelFeatureDataCoded.FeatureNames;
this.saveTreeBinFile = saveTreeBinFile;
this.saveTreeTextFile = saveTreeTextFile;
this.saveTreeXmlFile = saveTreeTextFile + ".xml";
}
/// <summary>
/// Compute and store the scores of the input data given a model
/// </summary>
/// <param name="model">the model to be evaluated</param>
/// <param name="labelFeatureData">input data</param>
/// <param name="subModelScore">pre-computed scores for the input data</param>
public void ModelEval(Model model, LabelFeatureData labelFeatureData, LabelFeatureData subModelScore)
{
if (subModelScore != null)
{
Debug.Assert(this.numSamples == subModelScore.NumDataPoint);
for (int i = 0; i < this.numSamples; i++)
{
this.score[i] = subModelScore.GetFeature(0, i);
}
}
else if (model != null && labelFeatureData != null)
{
Debug.Assert(this.numSamples == labelFeatureData.NumDataPoint);
float[] scores = new float[1];
for (int i = 0; i < this.numSamples; i++)
{
model.Evaluate(labelFeatureData.GetFeature(i), scores);
this.score[i] = scores[0];
}
}
else
{
for (int i = 0; i < this.numSamples; i++)
{
this.score[i] = 0.0F;
}
}
}
/// <summary>
/// Compute and store the scores of the input data given a model
/// </summary>
/// <param name="model">the model to be evaluated</param>
/// <param name="labelFeatureData">input data</param>
/// <param name="subModelScore">pre-computed scores for the input data</param>
public void ModelEval(Model model, LabelFeatureData labelFeatureData, LabelFeatureData subModelScore)
{
if (subModelScore != null)
{
Debug.Assert(this.numSamples == subModelScore.NumDataPoint);
for (int i = 0; i < this.numSamples; i++)
{
for (int k = 0; k < this.numClass; k++)
{
this.ModelScores[k][i] = subModelScore.GetFeature(k, i);
}
}
}
else if (model != null && labelFeatureData != null) // REVIEW by CJCB: this was 'if', I think it should be 'else if' so I changed it
{
Debug.Assert(this.numSamples == labelFeatureData.NumDataPoint);
float[] scores = new float[this.numClass];
for (int i = 0; i < this.numSamples; i++)
{
model.Evaluate(labelFeatureData.GetFeature(i), scores);
for (int k = 0; k < this.numClass; k++)
{
this.ModelScores[k][i] = scores[k];
}
}
}
else
{
//TODO: qiangwu - should we always requre subModel to exist
//to make the default model value computation explicit???
//It is probabaly safer that way revist the issue later
float score = (float)1.0 / (float)this.numClass;
for (int i = 0; i < this.numSamples; i++)
{
for (int k = 0; k < this.numClass; k++)
{
this.ModelScores[k][i] = score;
}
}
}
}
/// <summary>
/// Compute and store the scores of the input data given a model
/// </summary>
/// <param name="model">the model to be evaluated</param>
/// <param name="data">input data</param>
public void ModelEval(Model model, float[][] data)
{
Debug.Assert(this.numSamples == data.Length);
}