Source code for cornac.models.global_avg.recom_global_avg

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import numpy as np

from ..recommender import Recommender
from ...exception import ScoreException


[docs]class GlobalAvg(Recommender): """Global Average baseline for rating prediction. Rating predictions equal to average rating of training data (not personalized). Parameters ---------- name: string, default: 'GlobalAvg' The name of the recommender model. """ def __init__(self, name="GlobalAvg"): super().__init__(name=name, trainable=False)
[docs] def score(self, user_idx, item_idx=None): """Predict the scores/ratings of a user for an item. Parameters ---------- user_idx: int, required The index of the user for whom to perform score prediction. item_idx: int, optional, default: None The index of the item for that to perform score prediction. If None, scores for all known items will be returned. Returns ------- res : A scalar or a Numpy array Relative scores that the user gives to the item or to all known items """ if item_idx is None: return np.full(self.train_set.num_items, self.train_set.global_mean) else: return self.train_set.global_mean