parameters: (self, X)
return_statement: return self.classes_.take(decisions, axis=0)
docstring: Predict class for X.
  
          Parameters
          ----------
          X : array-like of shape = [n_samples, n_features]
              The input samples.
  
          Returns
          -------
          y: array of shape = ["n_samples]
              The predicted values.
docstring_summary: Predict class for X.
docstring_tokens: Predict class for X .
function: def predict(self, X):
          """Predict class for X.
  
          Parameters
          ----------
          X : array-like of shape = [n_samples, n_features]
              The input samples.
  
          Returns
          -------
          y: array of shape = ["n_samples]
              The predicted values.
          """
          score = self.decision_function(X)
          decisions = self.loss_._score_to_decision(score)
          return self.classes_.take(decisions, axis=0)
function_tokens: def predict ( self , X ) : score = self . decision_function ( X ) decisions = self . loss_ . _score_to_decision ( score ) return self . classes_ . take ( decisions , axis = 0 )