code: def _binarize(dataset):
      positives = dataset.data >= 4.0
      dataset.data[positives] = 1.0
      dataset.data[np.logical_not(positives)] = -1.0
  
      return dataset
  
imports: import pickle
  import numpy
  import scipy.sparse
  from scipy import stats
  from sklearn.metrics import roc_auc_score
  from sklearn.model_selection import KFold, RandomizedSearchCV
  from lightfm.lightfm import LightFM
  from lightfm.datasets import fetch_movielens
  from lightfm.evaluation import auc_score, precision_at_k
label_desc: Use image node_id 3 for calling a global function with example usage: _binarize(dataset) and returns: dataset