code: def resetStats(self):
      
      self._stats = dict()
      self._internalStats = dict()
  
      self._internalStats['nInfersSinceReset'] = 0
      self._internalStats['nPredictions'] = 0
  
      #New prediction score
      self._internalStats['curPredictionScore2']     = 0
      self._internalStats['predictionScoreTotal2']   = 0
      self._internalStats['curFalseNegativeScore']   = 0
      self._internalStats['falseNegativeScoreTotal'] = 0
      self._internalStats['curFalsePositiveScore']   = 0
      self._internalStats['falsePositiveScoreTotal'] = 0
  
      self._internalStats['pctExtraTotal'] = 0
      self._internalStats['pctMissingTotal'] = 0
      self._internalStats['curMissing'] = 0
      self._internalStats['curExtra'] = 0
      self._internalStats['totalMissing'] = 0
      self._internalStats['totalExtra'] = 0
  
      # Sequence signature statistics. Note that we don't reset the sequence
      # signature list itself.
      self._internalStats['prevSequenceSignature'] = None
      if self.collectSequenceStats:
        self._internalStats['confHistogram'] = \
            numpy.zeros((self.numberOfCols, self.cellsPerColumn), dtype="float32")
docs: Reset the learning and inference stats. This will usually be called by
      user code at the start of each inference run (for a particular data set).