Machine Learning with Swift

Assignment step

Calculate new centroids of clusters:

var centroidsCount = [Double](repeating: 0.0, count: k) 
let rowStub = [Double](repeating: 0.0, count: d) 
var centroidsCumulative = [[Double]](repeating: rowStub, count: k) 
 
for (point, clusterID) in zip(data, clusters) { 
  centroidsCount[clusterID] += 1 
  centroidsCumulative[clusterID] = vecAdd(centroidsCumulative[clusterID], point) 
} 
 
var newCentroids = centroidsCumulative 
for (j, row) in centroidsCumulative.enumerated() { 
  for (i, element) in row.enumerated() { 
    let new = element/centroidsCount[j] 
    assert(!new.isNaN) 
    newCentroids[j][i] = new 
  } 
} 

After this, we have to check whether the new centroids are different from those previously calculated. If they are different, we perform another iteration ...