docstr: Method to initialize the model. Create and calculate a similarity matrix
docstr_tok: ["Method","to","initialize","the","model",".","Create","and","calculate","a","similarity","matrix"]
code: def init_model(self):
      """
      Method to initialize the model. Create and calculate a similarity matrix
  
      """
      super(ItemKNN, self).init_model()
  
      self.similar_items = defaultdict(list)
  
      # Set the value for k
      if self.k_neighbors is None:
          self.k_neighbors = int(np.sqrt(len(self.items)))
  
      self.si_matrix = self.compute_similarity(transpose=True)
  
      for i_id, item in enumerate(self.items):
          self.similar_items[i_id] = sorted(
              range(len(self.si_matrix[i_id])),
              key=lambda k: -self.si_matrix[i_id][k],
          )[1 : self.k_neighbors + 1]
  
file_path: CaseRecommender/caserec/recommenders/rating_prediction/itemknn.py
imports: from collections import defaultdict
  import numpy
  from caserec.utils.extra_functions import timed
  from caserec.recommenders.rating_prediction.base_knn import BaseKNN
label_desc: Use image node_id 2 for calling the ItemKNN obj's underlying member method code with example usage: obj.init_model() without return types