def getLabels(self, start=None, end=None):
if len(self._recordsCache) == <NUM_LIT:0>:<EOL><INDENT>return {<EOL>'<STR_LIT>': False,<EOL>'<STR_LIT>': []<EOL>}<EOL><DEDENT>try:<EOL><INDENT>start = int(start)<EOL><DEDENT>except Exception:<EOL><INDENT>start = <NUM_LIT:0><EOL><DEDENT>try:<EOL><INDENT>end = int(end)<EOL><DEDENT>except Exception:<EOL><INDENT>end = self._recordsCache[-<NUM_LIT:1>].ROWID<EOL><DEDENT>if end <= start:<EOL><INDENT>raise HTMPredictionModelInvalidRangeError("<STR_LIT>",<EOL>debugInfo={<EOL>'<STR_LIT>': {<EOL>'<STR_LIT>': start,<EOL>'<STR_LIT>': end<EOL>},<EOL>'<STR_LIT>': len(self._recordsCache)<EOL>})<EOL><DEDENT>results = {<EOL>'<STR_LIT>': False,<EOL>'<STR_LIT>': []<EOL>}<EOL>ROWIDX = numpy.array(<EOL>self._knnclassifier.getParameter('<STR_LIT>'))<EOL>validIdx = numpy.where((ROWIDX >= start) & (ROWIDX < end))[<NUM_LIT:0>].tolist()<EOL>categories = self._knnclassifier.getCategoryList()<EOL>for idx in validIdx:<EOL><INDENT>row = dict(<EOL>ROWID=int(ROWIDX[idx]),<EOL>labels=self._categoryToLabelList(categories[idx]))<EOL>results['<STR_LIT>'].append(row)<EOL><DEDENT>return results<EOL>
Get the labels on classified points within range start to end. Not inclusive
of end.

:returns: (dict) with format:

  ::

    {
      'isProcessing': boolean,
      'recordLabels': list of results
    }

  ``isProcessing`` - currently always false as recalculation blocks; used if
  reprocessing of records is still being performed;

  Each item in ``recordLabels`` is of format:

  ::

    {
      'ROWID': id of the row,
      'labels': list of strings
    }