} // Main
static int Classify(double[] unknown, double[][] trainData, int numClasses, int k)
{
// compute and store distances from unknown to all train data
int n = trainData.Length; // number data items
IndexAndDistance[] info = new IndexAndDistance[n];
for (int i = 0; i < n; ++i)
{
IndexAndDistance curr = new IndexAndDistance();
double dist = Distance(unknown, trainData[i]);
curr.idx = i;
curr.dist = dist;
info[i] = curr;
}
Array.Sort(info); // sort by distance
Console.WriteLine("\nNearest / Distance / Class");
Console.WriteLine("==============================");
for (int i = 0; i < k; ++i)
{
int c = (int)trainData[info[i].idx][2];
string dist = info[i].dist.ToString("F3");
Console.WriteLine("( " + trainData[info[i].idx][0] + "," + trainData[info[i].idx][1] + " ) : " + dist + " " + c);
}
int result = Vote(info, trainData, numClasses, k); // k nearest classes
return(result);
} // Classify
static int Classify(double[] unknown, double[][] trainData, int numClasses, int k)
{
int n = trainData.Length;
IndexAndDistance[] info = new IndexAndDistance[n];
for (int i = 0; i < n; ++i)
{
IndexAndDistance curr = new IndexAndDistance();
double dist = Distance(unknown, trainData[i]);
curr.idx = i;
curr.dist = dist;
info[i] = curr;
}
int result = Vote(info, trainData, numClasses, k);
return(result);
}
