code: def metrics_plot(
      model_names,
      coverage_scores,
      personalization_scores,
      intra_list_similarity_scores,
  ):
      """
      Plots the coverage, personalization and intra-list similarity for a set of models to compare.
      ----------
      model_names: list
          list of model names in same order as coverage_scores
          example: ['Model A', 'Model B', 'Model C']
      coverage_scores: list
          list of scores in same order as model_names
          example: [0.17, 0.25, 0.76]
      personalization_scores: list
          list of scores in same order as model_names
          example: [0.43, 0.23, 0.44]
      intra_list_similarity: list
          list of scores in same order as model_names
          example: [0.23, 0.21, 0.69]
      Returns:
      -------
          An interactive metrics plot
      """
  
      fig = go.Figure()
  
      for (
          model_name,
          coverage,
          personalization,
          intra_list_similarity,
      ) in zip(
          model_names,
          coverage_scores,
          personalization_scores,
          intra_list_similarity_scores,
      ):
          fig.add_trace(
              go.Scatterpolar(
                  r=[
                      coverage,
                      personalization * 100,
                      intra_list_similarity * 100,
                  ],
                  theta=[
                      "coverage",
                      "personalization",
                      "intra list similarity",
                  ],
                  fill="tonext",
                  name=model_name,
              )
          )
  
      fig.update_layout(
          polar=dict(radialaxis=dict(visible=True, range=[0, 100])),
          showlegend=True,
      )
  
      fig.show()
  
imports: import matplotlib.pyplot
  import numpy
  import pandas
  import plotly.graph_objects
  import seaborn
  from funcsigs import signature
  from matplotlib.lines import Line2D
  from sklearn.metrics import auc, average_precision_score, precision_recall_curve, roc_curve
label_desc: Use image node_id 12 for calling a global function with example usage: metrics_plot(model_names, coverage_scores, personalization_scores, intra_list_similarity_scores) without return types