class_docstr: Represent the prediction results of user-item pairs.
  
  Each prediction record will contain the following information:
  user_id: Positive int.
  item_id: Positive int.
  prediction: The prediction (rating) for the user on the item.
  probability: The probability for the prediction.
class_docstr_tok: ["Represent","the","prediction","results","of","user-item","pairs",".","Each","prediction","record","will","contain","the","following","information",":","user_id",":","Positive","int",".","item_id",":","Positive","int",".","prediction",":","The","prediction","(","rating",")","for","the","user","on","the","item",".","probability",":","The","probability","for","the","prediction","."]
code: def __init__(
      self,
      user_id,
      item_id,
      prediction,
      probability,
      bigdl_type="float",
  ):
      self.user_id = user_id
      self.item_id = item_id
      self.prediction = prediction
      self.probability = probability
      self.bigdl_type = bigdl_type
  
imports: import sys
  from pyspark import RDD
  from zoo.models.common import *
  from zoo.common.utils import callZooFunc
label_desc: Use image node_id 1 to create a new UserItemPrediction object from inherited base classes: object with example: obj = UserItemPrediction(user_id, item_id, prediction, probability, bigdl_type)