class_docstr: Normalized Discount Cumulative Gain.
  
  Parameters
  ----------
  k: int or list, optional, default: -1 (all)
      The number of items in the top@k list.
      If None, all items will be considered.
  
  References
  ----------
  https://en.wikipedia.org/wiki/Discounted_cumulative_gain
class_docstr_tok: ["Normalized","Discount","Cumulative","Gain",".","Parameters","--","--","--","--","--","k",":","int","or","list",",","optional",",","default",":","-1","(","all",")","The","number","of","items","in","the","top","@","k","list",".","If","None",",","all","items","will","be","considered",".","References","--","--","--","--","--","https",":","\/\/en.wikipedia.org\/wiki\/Discounted_cumulative_gain"]
code: def __init__(self, k=-1):
      RankingMetric.__init__(self, name="NDCG@{}".format(k), k=k)
  
imports: import numpy
  from scipy.stats import rankdata
label_desc: Use image node_id 1 to create a new NDCG object from inherited base classes: RankingMetric with example: obj = NDCG(k)