Detecting/identifying number of clusters present in dataset about ai4r HOT 3 OPEN

def self.create_best_cluster(data)
    cluster = Ai4r::Clusterers::KMeans.new
    dataset = Ai4r::Data::DataSet.new
    dataset.set_data_items(data)
    cluster_fitness = []

    10.times do |t|
      cluster.build(dataset,t+1)
      cluster_fitness[t] = 0
      dataset.data_items.each do |item|
        cluster_fitness[t] += cluster.distance(cluster.centroids[cluster.eval(item)],item)
      end
    end
    #when derivative gets below 0.05: the next additional cluster did not improve the fitness significant, so the best fitting cluster is the array index + 2 as the array start's at 0 but clustering start's at 1
    cluster.build(dataset, cluster_fitness.each_cons(2).map{|x, y| y - x}.map.with_index{|derivate,index| derivate.abs >= 0.05 ? index : nil}.compact.max + 2)
  end