class_docstr: Evaluate metrics for y_true and y_pred.
code: def get_metric_mode(metric):
      Evaluator.check_metric(metric)
      if metric in Evaluator.max_mode_metrics:
          return "max"
      else:
          return "min"
  
imports: from sklearn.metrics import mean_squared_error
  from sklearn.metrics import r2_score
  from sklearn.metrics import mean_absolute_error
  from sklearn.metrics import mean_squared_log_error
  import numpy
  import pandas
label_desc: Use image node_id 3 for calling the Evaluator obj's underlying member method code with example usage: obj.get_metric_mode(metric) and returns: str, str