public void UtgAction()
{
LimitFeatureGenerator _featureGen = new LimitFeatureGenerator() { SkipMissingFeatures = true };
var hand = buildHand(utg);
var data = _featureGen.GenerateClassifierInstances(0);
_featureGen.GenerateFeatures(hand, 0, 0, data, false);
}
public WekaPlayer(string preflopModelFile, string flopModelFile,
string turnModelFile, string riverModelFile)
{
if(_featureGen == null)
_featureGen = new LimitFeatureGenerator() { SkipMissingFeatures = true };
if(_models == null)
{
_models = new Classifier[4];
_models[0] = (Classifier)weka.core.SerializationHelper.read(preflopModelFile);
_models[1] = (Classifier)weka.core.SerializationHelper.read(flopModelFile);
_models[2] = (Classifier)weka.core.SerializationHelper.read(turnModelFile);
_models[3] = (Classifier)weka.core.SerializationHelper.read(riverModelFile);
}
if(_instances == null)
{
_instances = new Instances[4];
for(int i = 0; i < 4; i++)
_instances[i] = _featureGen.GenerateInstances(i);
}
}
public NeuralNetworkPlayer(FeedForwardNeuralNetwork network)
{
_network = network;
_featureGen = new LimitFeatureGenerator();
}