//Methods
/// <summary>
/// Adds the cluster into the chain.
/// </summary>
/// <param name="cluster">The cluster to be added into the chain.</param>
public void AddCluster(TNRNetCluster cluster)
{
_clusterCollection.Add(cluster);
return;
}
/// <summary>
/// Builds the cluster.
/// </summary>
/// <param name="dataBundle">The data bundle for training.</param>
/// <param name="filters">The filters to be used to denormalize outputs.</param>
public TNRNetCluster Build(VectorBundle dataBundle, FeatureFilterBase[] filters)
{
VectorBundle localDataBundle = dataBundle.CreateShallowCopy();
//Cluster of trained networks
TNRNetCluster cluster = new TNRNetCluster(_clusterName,
_clusterCfg.Output,
_clusterCfg.TrainingGroupWeight,
_clusterCfg.TestingGroupWeight,
_clusterCfg.SamplesWeight,
_clusterCfg.NumericalPrecisionWeight,
_clusterCfg.MisrecognizedFalseWeight,
_clusterCfg.UnrecognizedTrueWeight
);
//Member's training
ResetProgressTracking();
for (_repetitionIdx = 0; _repetitionIdx < _crossvalidationCfg.Repetitions; _repetitionIdx++)
{
//Data split to folds
List <VectorBundle> foldCollection = localDataBundle.Folderize(_crossvalidationCfg.FoldDataRatio, _clusterCfg.Output == TNRNet.OutputType.Real ? double.NaN : cluster.OutputDataRange.Mid);
_numOfFoldsPerRepetition = Math.Min(_crossvalidationCfg.Folds <= 0 ? foldCollection.Count : _crossvalidationCfg.Folds, foldCollection.Count);
//Train the collection of networks for each processing fold.
for (_testingFoldIdx = 0; _testingFoldIdx < _numOfFoldsPerRepetition; _testingFoldIdx++)
{
//Prepare training data bundle
VectorBundle trainingData = new VectorBundle();
for (int foldIdx = 0; foldIdx < foldCollection.Count; foldIdx++)
{
if (foldIdx != _testingFoldIdx)
{
trainingData.Add(foldCollection[foldIdx]);
}
}
for (_netCfgIdx = 0; _netCfgIdx < _clusterCfg.ClusterNetConfigurations.Count; _netCfgIdx++)
{
TNRNetBuilder netBuilder = new TNRNetBuilder(_clusterName,
_clusterCfg.ClusterNetConfigurations[_netCfgIdx],
_clusterCfg.Output,
trainingData,
foldCollection[_testingFoldIdx],
_rand,
_controller
);
//Register notification
netBuilder.NetworkBuildProgressChanged += OnNetworkBuildProgressChanged;
//Build trained network. Trained network becomes to be the cluster member
TNRNet tn = netBuilder.Build();
//Build an unique network scope identifier
int netScopeID = _repetitionIdx * NetScopeDelimiterCoeff + _testingFoldIdx;
//Add trained network to a cluster
cluster.AddMember(tn, netScopeID, foldCollection[_testingFoldIdx], filters);
} //netCfgIdx
} //testingFoldIdx
if (_repetitionIdx < _crossvalidationCfg.Repetitions - 1)
{
//Reshuffle the data
localDataBundle.Shuffle(_rand);
}
}//repetitionIdx
//Make the cluster operable
cluster.FinalizeCluster();
//Return the built cluster
return(cluster);
}