code: def plot_threshold_vs_accuracy_curve(
      accuracies, thresholds, graph_path, title
  ):
      plt.clf()
      plt.plot(thresholds, accuracies, label="ROC curve")
      plt.xlabel("Threshold")
      plt.ylabel("Accuracy")
      plt.ylim([0.0, 1.05])
      plt.xlim([0.0, 1.0])
      plt.title(title)
      plt.legend(loc="lower left")
      plt.savefig(
          graph_path, dpi=600, format="pdf", bbox_inches="tight"
      )  # use format='svg' or 'pdf' for vectorial pictures
      plt.close()
  
file_path: NeuroNER/neuroner/utils_plots.py
imports: from __future__ import print_function
  from __future__ import division
  import matplotlib
  from matplotlib import cm
  import matplotlib.pyplot
  import numpy
  import sklearn.preprocessing
label_desc: Use image node_id 10 for calling a global function with example usage: plot_threshold_vs_accuracy_curve(accuracies, thresholds, graph_path, title) without return types