/// <summary>
/// Отобразить кластеры рекурсивно.
/// </summary>
/// <param name="cluster">Кластер для отображения.</param>
/// <param name="parentNode">Родительская вершина дерева.</param>
private void DrawClustersRecursive(NetworkCluster cluster, TreeNode parentNode)
{
var index = parentNode.Nodes.Add(new TreeNode
{
Text = $"{cluster.Number} ({cluster.Entities?.Count ?? 0})",
Tag = cluster
});
if (!(cluster.Clusters?.Any() ?? false))
{
return;
}
foreach (var subCluster in cluster.Clusters)
{
DrawClustersRecursive(subCluster, parentNode.Nodes[index]);
}
}
/// <summary>
/// Тестировать сеть рекурсивно.
/// </summary>
/// <param name="cluster">Текущий кластер.</param>
private void TestDataRecursive(NetworkCluster cluster)
{
if (!(cluster.Entities?.Any() ?? false) ||
!(cluster.Clusters?.Any() ?? false) ||
cluster.NetworkId == null)
{
return;
}
cluster.Clusters.ForEach(c => c.Entities.Clear());
var currentNetworkData = _networkService.GetNetworkData(cluster.NetworkId.Value);
var neuralNetwork = IoC.Instance.Resolve<AbstractNetwork>();
neuralNetwork.InitializeNetwork(
currentNetworkData.Neurons.Select(e => e.Neuron).ToList(),
currentNetworkData.InputAttributes,
currentNetworkData.Weights);
RecalcMinMaxValues(cluster.Entities);
foreach (var data in cluster.Entities)
{
var attributeValues = data.AttributeValues
.Select(attr => new InputAttributeValue
{
InputAttributeNumber = attr.Attribute.OrderNumber,
Value = attr.GetNormalizedValue(_neuralNetwork.NormalizationType)
})
.ToList();
var result = neuralNetwork.GetNeuronWinner(attributeValues).NeuronNumber;
cluster.Clusters.First(c => c.Number == result).Entities.Add(data);
}
foreach (var subCluster in cluster.Clusters)
{
TestDataRecursive(subCluster);
}
}
