public void KNearestNeighborsTest()
{
Tuple <double[], double> tuple1 = new Tuple <double[], double>(new double[] { 3, 104, 2 }, 0);
Tuple <double[], double> tuple2 = new Tuple <double[], double>(new double[] { 2, 100, 1 }, 0);
Tuple <double[], double> tuple3 = new Tuple <double[], double>(new double[] { 1, 81, 0 }, 0);
Tuple <double[], double> tuple4 = new Tuple <double[], double>(new double[] { 101, 10, 0 }, 1);
Tuple <double[], double> tuple5 = new Tuple <double[], double>(new double[] { 99, 5, 0 }, 1);
Tuple <double[], double> tuple6 = new Tuple <double[], double>(new double[] { 98, 2, 0 }, 1);
Tuple <double[], double> tuple7 = new Tuple <double[], double>(new double[] { 3, 2, 20 }, 2);
Tuple <double[], double> tuple8 = new Tuple <double[], double>(new double[] { 4, 2, 21 }, 2);
Tuple <double[], double> tuple9 = new Tuple <double[], double>(new double[] { 2, 2, 23 }, 2);
List <Tuple <double[], double> > movies =
new List <Tuple <double[], double> >()
{
tuple1, tuple2, tuple3, tuple4, tuple5, tuple6, tuple7, tuple8, tuple9
};
KNearestNeighborsClassifier kNearestNeighborsClassifier =
new KNearestNeighborsClassifier(movies, 3, new EuclideMetric());
var result = kNearestNeighborsClassifier.Classify(new double[] { 3, 104, 2 });
result = kNearestNeighborsClassifier.Classify(new double[] { 101, 10, 0 });
result = kNearestNeighborsClassifier.Classify(new double[] { 80, 10, 0 });
result = kNearestNeighborsClassifier.Classify(new double[] { 5, 90, 1 });
result = kNearestNeighborsClassifier.Classify(new double[] { 4, 2, 21 });
result = kNearestNeighborsClassifier.Classify(new double[] { 3, 3, 25 });
}
private SmartphonePositions AnalyzeAccelerometerData(IEnumerable <ICoorinateContainer> coordinates)
{
if (coordinates == null || coordinates.Count() == 0)
{
return(SmartphonePositions.Not_Found);
}
return(KNearestNeighborsClassifier.GetInstance().DefineMove(coordinates));
}
public static string RunTest()
{
string res;
//var fn = @"train.csv";
//var f = File.ReadLines(fn);
//var data = from z in f.Skip(1)
// let zz = z.Split(',').Select(int.Parse)
// select new
// {
// Label = zz.First(),
// Image = zz.Skip(1).ToArray()
// };
//var classefier = new MuliclassSupportVectorLearning<Linear>();
//classefier.Learn(,)
//var testData = new TestDataFileReader().GetTestData()
// .OrderBy(a => Guid.NewGuid()).ToList(); // shuffle
//SensorsDataModel model = new SensorsDataModel();
//StringBuilder res = new StringBuilder();
//foreach (var test in testData)
//{
// SmartphonePositions position = model.AnalyzeAccelerometerData(test.AccelerometerDataRecords
// .Select(d => new AccelerometerDataRecord { X = d.X, Y = d.Y, Z = d.Z }).ToList());
// res.Append($"{test.SmartphonePosition} -> {position} </br>");
//}
var testDataReader = new TestDataFileReader();
var testDataPath = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "learning_data", "test", "sample.out");
var coordinates = testDataReader.ParseCoordinatesFromString(File.ReadAllText(testDataPath));
var move = KNearestNeighborsClassifier.GetInstance().DefineMove(coordinates);
res = move.ToString();
return(res);
}
