Is there a name for the following (extremely simple) threshold-based clustering algorithm?
It does a pass over the data and creates a new cluster when no previous cluster is within a given distance threshold. Otherwise it assigns the point to the first close-enough cluster.
It's good enough if the data is already very well grouped and the within-cluster distances are only due to some tiny noise.
def cluster(data_points, threshold): cluster_prototypes =  labels =  for p in data_points: label = None for i, c in enumerate(cluster_prototypes): if distance(p, c) < threshold: label = i break if label is None: label = len(cluster_prototypes) cluster_prototypes.append(p) labels.append(label) return labels