#NEWLINE# def train( self , ppc = None , uncovered_dupes = None , maximum_comparisons = 1000000 , recall = 0.95 , index_predicates = True ) : #NEWLINE# #INDENT# 'Keyword arguments:\n\n        maximum_comparisons -- The maximum number of comparisons a\n                               blocking rule is allowed to make.\n\n                               Defaults to 1000000\n\n        recall -- The proportion of true dupe pairs in our training\n                  data that that we the learned blocks must cover. If\n                  we lower the recall, there will be pairs of true\n                  dupes that we will never directly compare.\n\n                  recall should be a float between 0.0 and 1.0, the default\n                  is 0.975\n\n        index_predicates -- Should dedupe consider predicates that\n                            rely upon indexing the data. Index predicates can\n                            be slower and take susbstantial memory.\n\n                            Defaults to True.\n        ' #NEWLINE# if ( ppc is not None ) : #NEWLINE# #INDENT# warnings . warn ( '`ppc` is a deprecated argument to train. Use `maximum_comparisons` to set the maximum number records a block is allowed to cover' ) #NEWLINE# #UNINDENT# if ( uncovered_dupes is not None ) : #NEWLINE# #INDENT# warnings . warn ( '`uncovered_dupes` is a deprecated argument to train. Use recall to set the proportion of true pairs that the blocking rules must cover' ) #NEWLINE# #UNINDENT# self . _trainClassifier ( ) #NEWLINE# self . _trainBlocker ( maximum_comparisons , recall , index_predicates )