public void TestObjectiveParametersDefault()
{
var x = new ObjectiveParameters();
var result = new Dictionary <string, string>();
x.AddParameters(result);
Assert.Empty(result);
}
private protected TrainerBase(LearningParameters lp, ObjectiveParameters op)
{
Learning = lp;
Objective = op;
//ParallelTraining = Args.ParallelTrainer != null ? Args.ParallelTrainer.CreateComponent(env) : new SingleTrainer();
//InitParallelTraining();
}
public RankingTrainer(LearningParameters lp, ObjectiveParameters op) : base(lp, op)
{
if (op.Objective != ObjectiveType.LambdaRank)
{
throw new Exception("Require Objective == ObjectiveType.LambdaRank");
}
if (op.Metric == MetricType.DefaultMetric)
{
op.Metric = MetricType.Ndcg;
}
}
public BinaryTrainer(LearningParameters lp, ObjectiveParameters op) : base(lp, op)
{
if (op.Objective != ObjectiveType.Binary)
{
throw new Exception("Require Objective == ObjectiveType.Binary");
}
if (op.Metric == MetricType.DefaultMetric)
{
op.Metric = MetricType.BinaryLogLoss;
}
}
public MulticlassTrainer(LearningParameters lp, ObjectiveParameters op) : base(lp, op)
{
if (!(op.Objective == ObjectiveType.MultiClass || op.Objective == ObjectiveType.MultiClassOva))
{
throw new Exception("Require Objective == MultiClass or MultiClassOva");
}
if (op.NumClass <= 1)
{
throw new Exception("Require NumClass > 1");
}
if (op.Metric == MetricType.DefaultMetric)
{
op.Metric = MetricType.MultiLogLoss; // TODO: why was this MultiError?????
}
}
public RegressionTrainer(LearningParameters lp, ObjectiveParameters op) : base(lp, op)
{
if (!(op.Objective == ObjectiveType.Regression ||
op.Objective == ObjectiveType.RegressionL1 ||
op.Objective == ObjectiveType.Huber ||
op.Objective == ObjectiveType.Fair ||
op.Objective == ObjectiveType.Poisson ||
op.Objective == ObjectiveType.Quantile ||
op.Objective == ObjectiveType.Mape ||
op.Objective == ObjectiveType.Gamma ||
op.Objective == ObjectiveType.Tweedie
))
{
throw new Exception("Require regression ObjectiveType");
}
if (op.Metric == MetricType.DefaultMetric)
{
op.Metric = MetricType.Mse;
}
}
