/// <summary>
/// Deserialize from an xml node.
/// </summary>
/// <param name="binaryClassifierNode">an xml node</param>
/// <returns>BinaryClassifier</returns>
public static BinaryClassifier DeserializeFromXML(XmlElement binaryClassifierNode)
{
double posLabel = double.NaN;
double negLabel = double.NaN;
StrongLeaner strongLearner = null;
foreach (XmlElement node in binaryClassifierNode.ChildNodes)
{
switch (node.Name)
{
case "PosLabel":
posLabel = double.Parse(node.InnerText);
break;
case "NegLabel":
negLabel = double.Parse(node.InnerText);
break;
case "StrongLearner":
Assembly asm = Assembly.GetAssembly(typeof(StrongLeaner));
strongLearner = (StrongLeaner)asm.CreateInstance(typeof(StrongLeaner).Namespace + "." + node.Attributes["type"].Value);
strongLearner.DerializeFromXML(node);
break;
}
}
return(new BinaryClassifier(posLabel, negLabel, strongLearner));
}
/// <summary>
/// Train posLabel vs negLabel.
/// when negLabel is NaN, Train posLabel vs other.
/// </summary>
/// <param name="prob">The training data</param>
/// <param name="arg">The training argument</param>
/// <param name="posLabel">positive label</param>
/// <param name="negLabel">negative label</param>
/// <returns>BinaryClassifier</returns>
public static BinaryClassifier Train(Problem prob, TrainingArg arg, double posLabel, double negLabel = double.NaN)
{
Problem binaryProb = CreatBinaryProblem(prob, posLabel, negLabel);
Assembly asm = Assembly.GetAssembly(typeof(StrongLeaner));
StrongLeaner strongLearner = (StrongLeaner)asm.CreateInstance(typeof(StrongLeaner).Namespace + "." + arg.StrongLearnerName);
strongLearner.Train(binaryProb, arg.WeakLearnerName, arg.WeakLearnerArgs, arg.Iterations);
return(new BinaryClassifier(posLabel, negLabel, strongLearner));
}
private BinaryClassifier(double posLabel, double negLabel, StrongLeaner strongLearner)
{
_posLabel = posLabel;
_negLabel = negLabel;
_strongLearner = strongLearner;
}
private BinaryClassifier(double posLabel, double negLabel, StrongLeaner strongLearner)
{
_posLabel = posLabel;
_negLabel = negLabel;
_strongLearner = strongLearner;
}