static void Main(string[] args)
{
int[] a = { 4, 2, 1, 7, 9, 8, 5, 3, 1, 0, -5, -19, 5, 2, 6, 7, 8, 2, 23, 5, 8, 3, 10, -20 };
//Vector<int> v = new Vector<int>(a);
//foreach (var item in temp)
//{
// Console.WriteLine(item);
//}
//double b1, b0;
//LinearRegression linear = new LinearRegression();
//linear.LoadData("data1.csv");
//linear.Solve(out b0, out b1);
//Console.WriteLine("Y = "+b1+"*X"+(b0 < 0 ? " "+b0 : " +" + b0));
//var res = 145 * b1 + b0;
//Console.WriteLine(res);
//var temp = System.IO.File.ReadAllLines("test-features.txt");
//System.Text.StringBuilder builder = new System.Text.StringBuilder();
//foreach (var item in temp)
//{
// var str = item.Trim().Replace(' ', ',');
// builder.AppendLine(str);
//}
//System.IO.File.WriteAllText("test1.csv", "");
//System.IO.File.WriteAllText("test1.csv", builder.ToString());
NaiveBayes na = new NaiveBayes("data_banknote_authentication.csv", 0.8);
string[] labels = { "variance", "skewness", "curtosis", "entropy", "class" };
var summarize = na.summarizeByClass(na.TrainingSet);
for (int i = 0; i < summarize.Count; i++)
{
var item = summarize[i];
Console.WriteLine("class " + i + " : ");
for (int j = 0; j < item.Count; j++)
{
var item2 = item[j];
Console.WriteLine(labels[j] + " -> mean : " + item2.First + " | standard deviation : " + item2.Second);
}
Console.WriteLine();
}
Console.WriteLine("----------------------------------------------------------");
Vector <double> pred = na.Predictions(summarize, na.TestSet);
//foreach (var item in pred)
//{
// Console.Write(item + " ");
//}
Console.WriteLine();
Console.WriteLine("My Implement Accuracy : " + na.Accuracy(na.TestSet, pred).ToString("0.00") + "%");
//foreach (var item in temp)
//{
// Console.WriteLine(item);
//}
//Console.WriteLine(v.BinarySearch(23));
//Console.WriteLine(v.Count);
//Console.WriteLine(v.Capactity);
//int[][] G =
//{
// new int[] {0,1,0,0,0,0,1},
// new int[] {1,0,1,1,0,0,0},
// new int[] {0,1,0,0,0,0,0},
// new int[] {0,1,0,0,1,1,0},
// new int[] {0,0,0,1,0,0,0},
// new int[] {0,0,0,1,0,0,0},
// new int[] {1,0,0,0,0,0,0},
//};
//GraphSearch graph = new GraphSearch(G);
//graph.recursiveDfs(0);
//int[][] G1 = { new int[]{0, 4, 0, 0, 0, 0, 0, 8, 0},
// new int[]{4, 0, 8, 0, 0, 0, 0, 11, 0},
// new int[]{0, 8, 0, 7, 0, 4, 0, 0, 2},
// new int[]{0, 0, 7, 0, 9, 14, 0, 0, 0},
// new int[]{0, 0, 0, 9, 0, 10, 0, 0, 0},
// new int[]{0, 0, 4, 14, 10, 0, 2, 0, 0},
// new int[]{0, 0, 0, 0, 0, 2, 0, 1, 6},
// new int[]{8, 11, 0, 0, 0, 0, 1, 0, 7},
// new int[]{0, 0, 2, 0, 0, 0, 6, 7, 0}
// };
//GraphWithWeight GW = new GraphWithWeight(G1);
//var test = GW.Dijkstra_PriorityQueue(0, 8);
//Console.WriteLine(test);
//Console.WriteLine(GW.Prim(3));
//int[][] G2 =
//{
// new int[]{0, 8, 12, 0, 0, 0, 0, 0, 0},
// new int[]{8, 0, 13, 25, 9, 0, 0, 0, 0},
// new int[]{12, 13, 0, 14, 0, 0, 21, 0, 0},
// new int[]{0, 25, 14, 0, 20, 8, 12, 12, 16},
// new int[]{0, 9, 0, 20, 0, 19, 0, 0, 0},
// new int[]{0, 0, 0, 8, 19, 0, 0, 11, 0},
// new int[]{0, 0, 21, 12, 0, 0, 0, 0, 11},
// new int[]{0, 0, 0, 12, 0, 11, 0, 0, 9},
// new int[]{0, 0, 0, 16, 0, 0, 11, 9, 0}
//};
//GW = new GraphWithWeight(G2);
//Console.WriteLine(GW.Prim(4));
//Console.WriteLine(GW.Kruskal());
//Vector<SV> vector = new Vector<SV>();
//vector.Add(new SV() {a=1,b=100 });
//vector.Add(new SV() { a = 1, b = 100 });
//vector.Add(new SV() { a = 2, b = 200 });
//vector.Add(new SV() { a = 4, b = 300 });
//vector.Add(new SV() { a = 10, b = 600 });
//vector.Add(new SV() { a = 9, b = 1000 });
//vector.Add(new SV() { a = 5, b = 1200 });
//vector.Sort();
//foreach (var item in vector)
//{
// Console.WriteLine(item.a+" - "+item.b);
//
//GeneralGraph MG = new GeneralGraph(6);
//MG.AddEdge(0, 1);
//MG.AddEdge(1, 2);
//MG.AddEdge(2, 0);
//MG.AddEdge(3, 4);
//MG.AddEdge(4, 5);
//MG.AddEdge(5, 3);
//int[] res;
//Console.WriteLine(MG.GetMaximumMatching(out res));
//foreach (var item in res)
//{
// Console.WriteLine(item);
//}
//Console.WriteLine(graph.BFS());
//var temp = graph.BFS(0, 5);
//foreach (var item in temp) Console.Write(item+" ");
//Vector<int> v = new Vector<int>();
//v[6] = 25;
//Console.WriteLine(v.Count + "|" + v.Capactity);
//foreach (var item in v)
//{
// Console.WriteLine(item);
//}
//Random rnd = new Random();
//for (int i = 0; i < a.Length; i++)
//{
// a[i] = rnd.Next(-100, 100);
//}
//var temp1 = (int[])a.Clone();
//var temp2 = (int[])a.Clone();
//var temp3 = (int[])a.Clone();
//Stopwatch timer = new Stopwatch();
//timer.Start();
//SortAlgo<int>.QuickSort(a, 0, a.Length - 1);
//timer.Stop();
//Console.WriteLine("Time : " + timer.ElapsedMilliseconds / 1000.00 + "s");
//timer.Start();
//SortAlgo<int>.HeapSort(temp1);
//timer.Stop();
//Console.WriteLine("Time : " + timer.ElapsedMilliseconds / 1000.00 + "s");
//timer.Start();
//SortAlgo<int>.MergeSort(temp2, 0, temp1.Length - 1);
//timer.Stop();
//Console.WriteLine("Time : " + timer.ElapsedMilliseconds / 1000.00 + "s");
//timer.Start();
//SortAlgo<int>.TimSort(temp3,1<<10);
//timer.Stop();
//Console.WriteLine("Time : " + timer.ElapsedMilliseconds / 1000.00 + "s");
//string a = "ababcab";
//a = "abc@" + a;
//foreach (var item in a.ToCharArray().ZAlgorithm())
//{
// Console.Write(item + " ");
//}
//Console.WriteLine(a.ZAlgoSearch("abc")[0]);
//Scanner scanner = new Scanner();
//int n = scanner.NextInt();
//int m = scanner.NextInt();
//List<PointInt2D> list = new List<PointInt2D>();
//for (int i = 0; i < n; i++)
//{
// PointInt2D tmp = new PointInt2D(scanner.NextLong(), scanner.NextLong());
// list.Add(tmp);
//}
//var covexHull = GeometryUtils.ConvexHull(list);
//foreach (var item in covexHull)
//{
// Console.WriteLine(item.ToString());
//}
//double res = Double.MaxValue;
//for (int i = 0; i < m; i++)
//{
// double S, d;
// PointInt2D tmp = new PointInt2D(scanner.NextLong(), scanner.NextLong());
// for (int j = 0; j < covexHull.Count - 1; j++)
// {
// S = GeometryUtils.TriangleDoubledSquare(tmp, covexHull[j], covexHull[j + 1]);
// d = Math.Sqrt(covexHull[j].DistDQ(covexHull[j + 1]));
// res = Math.Min(res, S / d);
// }
//}
//Console.WriteLine(res);
Console.ReadKey();
}
