public override Result Perform(InputData inputData)
{
int n, k;
NPoint[] x;
using (var sr = new StreamReader("input.txt"))
{
string f = sr.ReadLine();
n = int.Parse(f);
f = sr.ReadLine();
k = int.Parse(f);
x = new NPoint[n];
for (int i = 0; i < n; i++)
{
x[i] = new NPoint()
{
X = new double[k - 2]
}
}
;
for (int i = 0; i < n; i++)
{
var str = sr.ReadLine().Split(new char[] { ' ', '\t', ',' }, StringSplitOptions.RemoveEmptyEntries);
for (int j = 0; j < k - 2; j++)
{
x[i].X[j] = double.Parse(str[j], CultureInfo.InvariantCulture);
}
x[i].Class = str[str.Length - 1];
}
}
NPoint np1 = new NPoint()
{
X = new double[] { 5.7, 4.4 }
}; // Iris-setosa
NPoint np2 = new NPoint()
{
X = new double[] { 6.1, 2.8 }
}; // Iris-versicolor
NPoint np3 = new NPoint()
{
X = new double[] { 6.4, 2.8 }
}; // Iris-virginica
Methods.KNearestNeighbor(x.ToList(), np1, 30);
Methods.KNearestNeighbor(x.ToList(), np2, 30);
Methods.KNearestNeighbor(x.ToList(), np3, 30);
Console.WriteLine(np1.Class);
Console.WriteLine(np2.Class);
Console.WriteLine(np3.Class);
string s1 = Methods.BayesClassificator <string, NPoint>(x.ToList(), np1, c => c.Class);
string s2 = Methods.BayesClassificator <string, NPoint>(x.ToList(), np2, c => c.Class);
string s3 = Methods.BayesClassificator <string, NPoint>(x.ToList(), np3, c => c.Class);
Console.WriteLine(s1);
Console.WriteLine(s2);
Console.WriteLine(s3);
string[][] table;
using (var sr = new StreamReader("tree.txt", Encoding.Unicode))
{
string f = sr.ReadLine();
n = int.Parse(f);
f = sr.ReadLine();
k = int.Parse(f);
table = new string[n][];
for (int i = 0; i < n; i++)
{
table[i] = new string[k + 1];
}
for (int i = 0; i < n; i++)
{
var str = sr.ReadLine().Split(new char[] { ' ', '\t', ',' }, StringSplitOptions.RemoveEmptyEntries);
for (int j = 0; j < k + 1; j++)
{
table[i][j] = str[j];
}
}
}
Trees t = new Trees();
Node root = t.Build(table, new bool[k]);
string[] qwestion = { "Ниже", "ВГостях", "НаМесте ", "Нет", "" };
Console.WriteLine(root.Find(qwestion));
Console.ReadLine();
throw new NotImplementedException();
}
