private RandomForestModelSurrogate(RandomForestModelSurrogate original, Cloner cloner) : base(original, cloner)
{
IRandomForestModel clonedModel = null;
if (original.actualModel.IsValueCreated)
{
clonedModel = cloner.Clone(original.ActualModel);
}
actualModel = new Lazy <IRandomForestModel>(CreateLazyInitFunc(clonedModel)); // only capture clonedModel in the closure
// clone data which is necessary to rebuild the model
this.originalTrainingData = cloner.Clone(original.originalTrainingData);
this.seed = original.seed;
this.classValues = original.classValues;
this.nTrees = original.nTrees;
this.r = original.r;
this.m = original.m;
}
private IRandomForestModel RecalculateModel()
{
IRandomForestModel randomForestModel = null;
double rmsError, oobRmsError, relClassError, oobRelClassError;
var classificationProblemData = originalTrainingData as IClassificationProblemData;
if (originalTrainingData is IRegressionProblemData regressionProblemData)
{
randomForestModel = RandomForestRegression.CreateRandomForestRegressionModel(regressionProblemData,
nTrees, r, m, seed, out rmsError, out oobRmsError,
out relClassError, out oobRelClassError);
}
else if (classificationProblemData != null)
{
randomForestModel = RandomForestClassification.CreateRandomForestClassificationModel(classificationProblemData,
nTrees, r, m, seed, out rmsError, out oobRmsError,
out relClassError, out oobRelClassError);
}
return(randomForestModel);
}
public RandomForestClassificationSolution(IClassificationProblemData problemData, IRandomForestModel randomForestModel)
: base(randomForestModel, problemData) {
}
public RandomForestClassificationSolution(IClassificationProblemData problemData, IRandomForestModel randomForestModel)
: base(randomForestModel, problemData)
{
}
public RandomForestRegressionSolution(IRandomForestModel randomForestModel, IRegressionProblemData problemData)
: base(randomForestModel, problemData)
{
}
public RandomForestRegressionSolution(IRegressionProblemData problemData, IRandomForestModel randomForestModel)
: base(randomForestModel, problemData) {
}
// wrap an actual model in a surrograte
public RandomForestModelSurrogate(IRandomForestModel model, string targetVariable, IDataAnalysisProblemData originalTrainingData,
int seed, int nTrees, double r, double m, double[] classValues = null) : this(targetVariable, originalTrainingData, seed, nTrees, r, m, classValues)
{
actualModel = new Lazy <IRandomForestModel>(() => model);
}
private Func <IRandomForestModel> CreateLazyInitFunc(IRandomForestModel clonedModel)
{
return(() => {
return clonedModel ?? RecalculateModel();
});
}
