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  • Yue Zhao
  • pyod
  • Merge requests
  • !98

HBOS Categorical Implementation

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Open Yahya requested to merge github/fork/John-Almardeny/HBOS_Categorical_Features into development May 14, 2019
  • Overview 13
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All Submissions Basics:

Closes #21

  • Have you followed the guidelines in our Contributing document?
  • Have you checked to ensure there aren't other open Pull Requests for the same update/change?
  • Have you checked all Issues to tie the PR to a specific one?

All Submissions Cores:

  • Have you added an explanation of what your changes do and why you'd like us to include them?
  • Does your submission pass tests, including CircleCI, Travis CI, and AppVeyor?

New Model Submissions:

  • Have you created a _example.py in ~/examples/?
  • Have you lint your code locally prior to submission?

Description

There are several ways to convert categorical values to numerical ones in a given dataset, so HBOS can work with it.

I implemented 3 ways, left the option to the user to specify which by changing parameter category that has been added to HBOS Class. Methods are:

  1. One Hot Encoding.
  2. Label Encoding.
  3. Frequency Ratio Encoding.

Since, as far as I am ware of, PyOD does not provide synthesized categorical data (can be added on the list for future work ;-) ) , I tested the implementation on 3 different real-world categorical datasets, namely: Breast Cancer, Car Evaluation, Tic Tac Toe. Which can be found in HBOS_categorical_example.py file.

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Source branch: github/fork/John-Almardeny/HBOS_Categorical_Features