If I have some random data set let's say
X Y
1.2 16
5.7 0.256
128.54 6.879
0 2.87
6.78 0
2.98 3.7
... ...
x' y'
How can I find the centroid coordinates of this data set?
p.s. Here what I tried but got wrong results
float Dim1[K];
float Dim2[K];
float centroidD1[K];
float centroidD2[K];
int K = 4;
int counter[K];
for(int i = 0; i < K ; i++)
{
Dim1[i] = 0;
Dim2[i] = 0;
counter[i] = 0;
for(int j = 0; j < hash["Cluster"].size(); j++)
{
if(hash["Cluster"].value(j) == i+1)
{
Dim1[i] += hash["Dim_1"].value(j);
Dim2[i] += hash["Dim_2"].value(j);
counter[i]++;
}
}
}
for(int l = 0; l < K; l++)
{
centroidD1[l] = Dim1[l] / counter[l];
centroidD2[l] = Dim2[l] / counter[l];
}
I guess I choose wrong algorithm for doing it, as I get wrong results.
Calculating a sum and dividing by N is not a good idea if you have a large data set. As your floating point accumulator grows adding a new point eventually stop working due to the magnitude difference. An incremental formula might work better, see: https://math.stackexchange.com/questions/106700/incremental-averageing
If the issue is too large a data set you can verify the basic functioning of your code by using a smaller data set with a hand verified result. For example, just 1 data point, or 10 data points.