code: def plot_for_ensemble(scores, metric_name, model_path):
      plt.figure(figsize=(10, 7))
      plt.plot(range(1, len(scores) + 1), scores, label=f"Ensemble")
      plt.xlabel("#Iteration")
      plt.ylabel(metric_name)
      plt.legend(loc="best")
      plot_path = os.path.join(
          model_path, LearningCurves.output_file_name
      )
      plt.savefig(plot_path)
      plt.close("all")
  
file_path: mljar-supervised/supervised/utils/learning_curves.py
imports: import logging
  import os
  import numpy
  import pandas
  from supervised.utils.common import learner_name_to_fold_repeat
  from supervised.utils.config import LOG_LEVEL
  from supervised.utils.metric import Metric
  import matplotlib.colors
  import matplotlib.pyplot
label_desc: Use image node_id 5 for calling the LearningCurves obj's underlying member method code with example usage: obj.plot_for_ensemble(scores, metric_name, model_path) without return types