code: def ratio_multiplier(y):
      from collections import Counter
  
      multiplier = {1: 0.7, 2: 0.95}
      target_stats = Counter(y)
      for key, value in target_stats.items():
          if key in multiplier:
              target_stats[key] = int(value * multiplier[key])
      return target_stats
  
file_path: imbalanced-learn/examples/api/plot_sampling_strategy_usage.py
imports: import seaborn
  from sklearn.datasets import load_iris
  from imblearn.datasets import make_imbalance
  import matplotlib.pyplot
  from imblearn.under_sampling import RandomUnderSampler
  from imblearn.over_sampling import RandomOverSampler
  from imblearn.under_sampling import TomekLinks
label_desc: Use image node_id 1 for calling a global function with example usage: ratio_multiplier(y) and returns: target_stats