class_docstr: Normalized Cumulative Reciprocal Rank.
  
  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.
class_docstr_tok: ["Normalized","Cumulative","Reciprocal","Rank",".","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","."]
code: def __init__(self, k=-1):
      RankingMetric.__init__(self, name="NCRR@{}".format(k), k=k)
  
imports: import numpy
  from scipy.stats import rankdata
label_desc: Use image node_id 1 to create a new NCRR object from inherited base classes: RankingMetric with example: obj = NCRR(k)