static void Main(string[] args)
{
if (args.Length < 3)
{
Console.WriteLine("args");
Console.WriteLine("[TrainSet] [TestSet] [outfilename] [N]");
return;
}
TrainDataLoader loader = new TrainDataLoader();
var TrainSet = loader.LoadData(args[0]);
var TestSet = loader.LoadData(args[1]);
int n = 5;
if (args.Length == 4)
{
if (!int.TryParse(args[3], out n))
{
n = 5;
}
}
TestSet = TestSet.TakeEverNth(n).Cast <Point>().ToList();
goodRes = TestSet.Select(x => x.Cluster).ToArray();
test.GoodClassification = goodRes;
var alg = new AlgorithmEngine <Point, int>(2, 2, TrainSet, TestSet);
K_Test(alg, args[2]);
alg.K = 6;
P_Test(alg, args[2]);
All_Test(alg, args[2]);
Console.Read();
}
static void Main(string[] args)
{
string trainFilePath;
string testFilePath;
int k;
if (!CheckAndResolveArgs(args, out trainFilePath, out testFilePath, out k))
{
return;
}
TrainDataLoader dataLoader = new TrainDataLoader();
List <Point> trainData;
List <Point> testData;
try
{
trainData = dataLoader.LoadData(trainFilePath);
testData = dataLoader.LoadData(testFilePath);
}
catch (Exception e) {
Console.WriteLine(e.Message);
return;
}
AlgorithmEngine <Point, int> engine = new AlgorithmEngine <Point, int>(k, 2, trainData, testData);
var results = engine.KnnRunParallel();
PressAnyKey(false);
}