code: def correlation(oof1, oof2):
      cols = [c for c in oof1.columns if "prediction" in c]
      with warnings.catch_warnings():
          warnings.simplefilter(action="ignore")
          v = []
          for c in cols:
              c, _ = sp.stats.spearmanr(oof1[c], oof2[c])
              v += [c]
  
      return np.mean(v)
  
file_path: mljar-supervised/supervised/utils/automl_plots.py
imports: import logging
  import os
  import warnings
  import numpy
  import pandas
  import scipy
  from supervised.utils.config import LOG_LEVEL
  from supervised.utils.metric import Metric
  import warnings
  import matplotlib.pyplot
label_desc: Use image node_id 3 for calling the AutoMLPlots obj's underlying member method code with example usage: obj.correlation(oof1, oof2) and returns: np