docstr: Method to apply kmeans++ to rows and cols
docstr_tok: ["Method","to","apply","kmeans++","to","rows","and","cols"]
code: def run_kmeans(self):
      """
      Method to apply kmeans++ to rows and cols
  
      """
      clusters_rows = KMeans(
          n_clusters=self.k_row, init="k-means++"
      ).fit(self.matrix)
      clusters_cols = KMeans(
          n_clusters=self.l_col, init="k-means++"
      ).fit(self.matrix.T)
  
      # Map inverse index
      [
          self.list_row[label].append(row_id)
          for row_id, label in enumerate(clusters_rows.labels_)
      ]
      [
          self.list_col[label].append(col_id)
          for col_id, label in enumerate(clusters_cols.labels_)
      ]
  
file_path: CaseRecommender/caserec/clustering/paco.py
imports: import itertools
  import random
  import numpy
  from scipy.spatial.distance import squareform, pdist
  from sklearn.cluster import KMeans
  from caserec.utils.process_data import ReadFile
label_desc: Use image node_id 3 for calling the PaCo obj's underlying member method code with example usage: obj.run_kmeans() without return types