gistfile1.txt

# compute average hit rate for all users
def precision_at_k(predictions, k):
    '''
    Return the average ndcg for each users
    args:
        predictions: np.array user-item predictions
    returns:
        hit_rate: float, computed hit rate
    '''

    hit = 0
    
    # iterate
    for target_user in np.unique(val_user_ids):
        # get movie ids and ratings associated with the target user.
        target_val_movie_ids = val_movie_ids[val_user_ids == target_user] 
        target_val_ratings = val_ratings[val_user_ids == target_user] 
            
        clicked_movie_id = target_val_movie_ids[np.argmax(target_val_ratings)]
        predicted_order = np.argsort(-predictions[target_user])

        # if clicked id is within the top k prediction, hit += 1
        if np.where(predicted_order == clicked_movie_id)[0][0] < k:
            hit+=1
    
    
    return hit / (len(np.unique(val_user_ids)) * k)