public static void KnnMain()
{
Console.WriteLine("Using demo setup?[y/n]");
string str = Console.ReadLine();
if (str.ToLower().Contains("y") == false)
{
Console.WriteLine("Input node maximum value:(Default:10000)");
NodesMaxValueSet = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Input node count:(Default:150)");
NodesSet = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Input groups count for random points to divid into:(Default:3, Min:1)");
DataGroupCount = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Input fluctuation ratio:(Default:0.5, Min:0.1)");
FluctuationRatio = Convert.ToSingle(Console.ReadLine());
Console.WriteLine("Input new node count:(Default:10)");
NewNodesCount = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Input k set:(Default:7)");
k = Convert.ToInt32(Console.ReadLine());
}
//Gen grouped random nodes
Random2DPoints.OnGeneratePointGroups += Random2DPoints_OnGeneratePointGroups;
var ClassifiedPoints = Random2DPoints.GenerateRandomPointsGroup(NodesMaxValueSet, NodesSet, DataGroupCount, FluctuationRatio);
var Dataset = new VectorCollection <Point2D>(ClassifiedPoints);
Dataset.Print();
var knnTrainer = new KnnTrainer <Point2D>(Dataset);
Knn <Point2D> knn = new Knn <Point2D>(knnTrainer.Train());
knn.OnClassify += Knn_OnClassify;
while (Retry)
{
var NewNodes = Random2DPoints.GenerateRandomPoints(NodesMaxValueSet, NewNodesCount);
foreach (var NewNode in NewNodes)
{
knn.Classify(k, NewNode);
}
InputCommand();
}
}
public static void KmeansMain()
{
Console.WriteLine("Using demo setup?[y/n]");
string str = Console.ReadLine();
if (str.ToLower().Contains("y") == false)
{
Console.WriteLine("Input node maximum value:(Default:10000 , Min:0)");
NodesMaxValueSet = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Input node count:(Default:10000 , Min:0)");
NodesSet = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Input groups count for random points to divid into:(Default:3 , Min:0)");
DataGroupCount = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Input fluctuation ratio:(Default:0.18 , Min:0 , Max:0.5)");
FluctuationRatio = Convert.ToSingle(Console.ReadLine());
Console.WriteLine("Input k:( Default:3 , Min:1)");
k = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Input iteration limit:(Default:100)");
IterationLimit = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Input convergence distance:(Default:5)");
ConvDistance = Convert.ToInt32(Console.ReadLine());
}
//Gen grouped random nodes
Random2DPoints.OnGeneratePointGroups += Random2DPoints_OnGeneratePointGroups;
var RandomPoints = Random2DPoints.GenerateRandomPointsGroup(NodesMaxValueSet, NodesSet, DataGroupCount, FluctuationRatio);
var Dataset = new VectorCollection <Point2D>(RandomPoints);
Dataset.Print();
while (Retry)
{
KmeansTrainer <Point2D> kmeansTrainer = new KmeansTrainer <Point2D>(Dataset, k, ConvDistance, IterationLimit);
kmeansTrainer.OnIteration += Kmeans_OnIteration;
var TrainResult = kmeansTrainer.Train();
//Kmeans<Point2D> kmeans = new Kmeans<Point2D>(TrainResult);
InputCommand();
kmeansTrainer.OnIteration -= Kmeans_OnIteration;
}
}
