parameters: (self, X=None, Y=None)
return_statement: return score
docstring: Parameters
          ----------
          X : array-like of shape (n_samples, n_features)
              Input data, where n_samples is the number of samples and
              n_features is the number of features.
  
          Y : array-like of shape (n_samples, n_output) or (n_samples,), optional
              Target relative to X for classification or regression;
              None for unsupervised learning.
docstring_summary: Parameters
          ----------
          X : array-like of shape (n_samples, n_features)
              Input data, where n_samples is the number of samples and
              n_features is the number of features.
docstring_tokens: Parameters ---------- X : array - like of shape ( n_samples n_features ) Input data where n_samples is the number of samples and n_features is the number of features .
function: def score(self, X=None, Y=None):
          """
          Parameters
          ----------
          X : array-like of shape (n_samples, n_features)
              Input data, where n_samples is the number of samples and
              n_features is the number of features.
  
          Y : array-like of shape (n_samples, n_output) or (n_samples,), optional
              Target relative to X for classification or regression;
              None for unsupervised learning.
          """
          if self.foo_param > 1:
              score = 1.
          else:
              score = 0.
          return score
function_tokens: def score ( self , X = None , Y = None ) : if self . foo_param > 1 : score = 1. else : score = 0. return score