class_docstr: Class implementing the Perfect Tree Traversal strategy in PyTorch for isolation forest model.
class_docstr_tok: ["Class","implementing","the","Perfect","Tree","Traversal","strategy","in","PyTorch","for","isolation","forest","model","."]
code: def aggregation(self, x):
      output = x.sum(1)
      if self.final_probability_divider > 1:
          output = output / self.final_probability_divider
      # Further normalize to match "decision_function" in sklearn implementation.
      output = (
          -1.0 * 2 ** (-output / self.average_path_length) - self.offset
      )
      return output
  
imports: import numpy
  from onnxconverter_common.registration import register_converter
  from ..None import constants
  from .._tree_commons import get_parameters_for_sklearn_common, get_parameters_for_tree_trav_sklearn, get_tree_params_and_type, get_parameters_for_gemm_common
  from .._tree_implementations import TreeImpl, GEMMTreeImpl, TreeTraversalTreeImpl, PerfectTreeTraversalTreeImpl
label_desc: Use image node_id 2 for calling the PerfectTreeTraversalIsolationForestImpl obj's underlying member method code with example usage: obj.aggregation(x) and returns: output