docs: def rock(cls, data, eps, number_clusters, threshold=0.5, ccore=False):
          """
          Constructor of the ROCK cluster analysis algorithm
  
          :param eps: Connectivity radius (similarity threshold), points are neighbors if distance between them is less than connectivity radius
          :param number_clusters: Defines number of clusters that should be allocated from the input data set
          :param threshold: Value that defines degree of normalization that influences on choice of clusters for merging during processing
          :param ccore: Defines should be CCORE (C++ pyclustering library) used instead of Python code or not.
          :return: The resulting clustering.rst object
          """
          data = cls.input_preprocess(data)
          model = rock(data, eps, number_clusters, threshold, ccore)
          return cls(model)