class_docstr: Generator to give leave-one-out views on X.
  
  Parameters
  ----------
  X : array_like
      2-D array.
  
  Examples
  --------
  >>> X = np.random.normal(0, 1, [10,2])
  >>> loo = LeaveOneOut(X)
  >>> for x in loo:
  ...    print x
  
  Notes
  -----
  A little lighter weight than sklearn LOO. We do not need test index.
  Also passes views on X, not the index.
class_docstr_tok: ["Generator","to","give","leave-one-out","views","on","X.","Parameters","--","--","--","--","--","X",":","array_like","2-D","array",".","Examples","--","--","--","--",">",">",">","X","=","np.random.normal","(","0",",","1",",","[","10,2","]",")",">",">",">","loo","=","LeaveOneOut","(","X",")",">",">",">","for","x","in","loo",":","...","print","x","Notes","--","--","-","A","little","lighter","weight","than","sklearn","LOO",".","We","do","not","need","test","index",".","Also","passes","views","on","X",",","not","the","index","."]
code: def __init__(self, X):
      self.X = np.asarray(X)
  
imports: import copy
  import numpy
  from scipy import optimize
  from scipy.stats.mstats import mquantiles
  from .None import kernels
label_desc: Use image node_id 1 to create a new LeaveOneOut object  with example: obj = LeaveOneOut(X)