public static Dictionary <int, string> KnnCreate(Dictionary <List <string>, double[][]> trainingSet)
{
// Create some sample learning data.
int labelCounter = -1;
List <int> classesList = new List <int>();
Dictionary <int, string> labelMap = new Dictionary <int, string>();
foreach (string label in trainingSet.First().Key.ToArray())
{
if (!labelMap.ContainsValue(label))
{
labelCounter++;
classesList.Add(labelCounter);
labelMap.Add(labelCounter, label);
Console.WriteLine(labelCounter + ": " + label);
}
else
{
classesList.Add(labelCounter);
}
}
int[] classes = classesList.ToArray();
double[][] inputs = trainingSet.First().Value;
// Now we will create the K-Nearest Neighbors algorithm.
// It's possible to swtich around the k: 4 for the possibility of better accuracy
var knn = new KNearestNeighbors(k: 5);
// We train the algorithm:
knn.Learn(inputs, classes);
// Let's say we would like to compute the error matrix for the classifier:
var cm = GeneralConfusionMatrix.Estimate(knn, inputs, classes);
// We can use it to estimate measures such as
double error = cm.Error; // should be
double acc = cm.Accuracy; // should be
double kappa = cm.Kappa; // should be
Console.WriteLine("error: " + error);
Console.WriteLine("accuracy: " + acc);
Console.WriteLine("kappa: " + kappa);
Console.WriteLine("pearson: " + cm.Pearson);
for (int i = 0; i < cm.ColumnErrors.Length; i++)
{
if (cm.ColumnErrors[i] != 0)
{
double columnerror = double.Parse(cm.ColumnErrors[i].ToString()) / double.Parse(cm.ColumnTotals[i].ToString());
Console.WriteLine("Error of " + labelMap[i] + ": " + columnerror);
}
}
SaveKnn(knn);
Fingerprinting.WriteLabelMap(labelMap);
return(labelMap);
}
public static List <string> getOptions(double[] coordinates, KNearestNeighbors knn)
{
List <string> options = new List <string>();
Dictionary <int, string> labelMap = Fingerprinting.ReadLabelMap();
int[] list = labelMap.Keys.ToArray();
foreach (double[] g in knn.GetNearestNeighbors(coordinates, out list))
{
options.Add(getRoomname(knn.Decide(g)));
}
return(options);
}
public static string getRoomname(int roomInt)
{
Dictionary <int, string> labelMap = Fingerprinting.ReadLabelMap();
return(labelMap[roomInt]);
}
