class_docstr: Record of multiple executions of a single metric.
  
  It contains a collection of `MetricObservation` instances.
  
  Args:
      direction: String. The direction of the metric to optimize. The value
          should be "min" or "max".
class_docstr_tok: ["Record","of","multiple","executions","of","a","single","metric",".","It","contains","a","collection","of","`","MetricObservation","`","instances",".","Args",":","direction",":","String",".","The","direction","of","the","metric","to","optimize",".","The","value","should","be","``","min","''","or","``","max","''","."]
code: def get_statistics(self):
      history = self.get_history()
      history_values = [obs.mean() for obs in history]
      return (
          {
              "min": float(np.nanmin(history_values)),
              "max": float(np.nanmax(history_values)),
              "mean": float(np.nanmean(history_values)),
              "median": float(np.nanmedian(history_values)),
              "var": float(np.nanvar(history_values)),
              "std": float(np.nanstd(history_values)),
          }
          if len(history_values)
          else {}
      )
  
imports: import inspect
  import numpy
  import six
  from keras_tuner import protos
  from keras_tuner.api_export import keras_tuner_export
  from keras_tuner.backend import keras
label_desc: Use image node_id 7 for calling the MetricHistory obj's underlying member method code with example usage: obj.get_statistics() and returns: unknown