(self, data)
return sorted([(
            reduce(lambda x, y:x * y,
                   [
                       self.attr_status[i][data[i]][label]
                       for i in range(len(data))
                       if self.attr_status[i][data[i]].has_key(label)
                   ]
                   )
            *
            self.label_status[label], label
        )
            for label in self.label_status.keys()
        ], reverse=True)
对输入数据进行预测
            params:
                data
            return 
                label 数据标记
            raise
                None
对输入数据进行预测
            params:
                data
            return 
                label 数据标记
            raise
                None
对输入数据进行预测 params : data return label 数据标记 raise None
def predict_old(self, data):

        """对输入数据进行预测
            params:
                data
            return 
                label 数据标记
            raise
                None
        """
        return sorted([(
            reduce(lambda x, y:x * y,
                   [
                       self.attr_status[i][data[i]][label]
                       for i in range(len(data))
                       if self.attr_status[i][data[i]].has_key(label)
                   ]
                   )
            *
            self.label_status[label], label
        )
            for label in self.label_status.keys()
        ], reverse=True)
def predict_old ( self , data ) : return sorted ( [ ( reduce ( lambda x , y : x * y , [ self . attr_status [ i ] [ data [ i ] ] [ label ] for i in range ( len ( data ) ) if self . attr_status [ i ] [ data [ i ] ] . has_key ( label ) ] ) * self . label_status [ label ] , label ) for label in self . label_status . keys ( ) ] , reverse = True )