class_docstr: Common predictor for matrix factorization.
  
  Attributes:
      user_index_(pandas.Index): Users in the model (length=:math:`m`).
      item_index_(pandas.Index): Items in the model (length=:math:`n`).
      user_features_(numpy.ndarray): The :math:`m \times k` user-feature matrix.
      item_features_(numpy.ndarray): The :math:`n \times k` item-feature matrix.
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docstr: Look up the indices for a set of items.
  
  Args:
      items(array-like): the item IDs to look up.
  
  Returns:
      numpy.ndarray: the item indices. Unknown items will have negative indices.
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code: def lookup_items(self, items):
      """
      Look up the indices for a set of items.
  
      Args:
          items(array-like): the item IDs to look up.
  
      Returns:
          numpy.ndarray: the item indices. Unknown items will have negative indices.
      """
      return self.item_index_.get_indexer(items)
  
file_path: lkpy/lenskit/algorithms/mf_common.py
imports: import logging
  import numpy
  import pandas
  from .None import Predictor
label_desc: Use image node_id 5 for calling the MFPredictor obj's underlying member method code with example usage: obj.lookup_items(items) and returns: self