/// <summary>
/// Train a new decision forest given some training data and a training
/// problem described by an instance of the ITrainingContext interface.
/// </summary>
/// <param name="random">Random number generator.</param>
/// <param name="parameters">Training parameters.</param>
/// <param name="maxThreads">The maximum number of threads to use.</param>
/// <param name="context">An ITrainingContext instance describing
/// the training problem, e.g. classification, density estimation, etc. </param>
/// <param name="data">The training data.</param>
/// <returns>A new decision forest.</returns>
public static Forest <F, S> TrainForest(
Random random,
TrainingParameters parameters,
ITrainingContext <F, S> context,
int maxThreads,
IDataPointCollection data,
ProgressWriter progress = null)
{
if (progress == null)
{
progress = new ProgressWriter(parameters.Verbose?Verbosity.Verbose:Verbosity.Interest, Console.Out);
}
Forest <F, S> forest = new Forest <F, S>();
for (int t = 0; t < parameters.NumberOfTrees; t++)
{
progress.Write(Verbosity.Interest, "\rTraining tree {0}...", t);
Tree <F, S> tree = ParallelTreeTrainer <F, S> .TrainTree(random, context, parameters, maxThreads, data, progress);
forest.AddTree(tree);
}
progress.WriteLine(Verbosity.Interest, "\rTrained {0} trees. ", parameters.NumberOfTrees);
return(forest);
}
