yzhao062/pyod

specifying categorical features in Python Outlier Detection (PyOD)

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#21 建立於 2018年9月14日

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 (5 留言) (0 反應) (1 負責人)Python (7,762 star) (1,308 fork)batch import
enhancementhelp wanted

描述

How to specify the categorical features in PyOD when using Histogram-based Outlier Detection (HBOS) for anomaly detection ? I've read that HBOS can be used for anomaly detection when there are categorical features involved. I found it's Python implementation here: https://pyod.readthedocs.io/en/latest/pyod.models.html#module-pyod.models.hbos But I can't figure out how should I pass the position or list of names of categorical features of my dataset while training the model. The code I've tried:

clf = HBOS(n_bins=10, alpha=0.1, tol=0.5, contamination=0.1)
clf.fit(train_df)
train_pred = clf.labels_

There is no parameter to mention categorical features while training.

貢獻者指南

技術棧
python
領域
datamachine learning
議題類型
feature
難度面向新貢獻者的預計實作難度，1 表示很小改動，5 表示專家級工作。
3
預計時間有經驗貢獻者完成調查、實作、測試並準備 pull request 的粗略時間範圍。
half day
活動狀態議題目前的可參與程度：新鮮、活躍、陳舊、阻塞或等待維護者輸入。
stale
清晰度議題是否清楚說明預期改動、驗收標準和下一步。
clear
前置要求
Basic PythonFamiliarity with PyODUnderstanding of HBOS
新手友善度1-100 的估計分數，表示該議題對首次貢獻者的友善程度。
40
研究方向
Investigate the HBOS implementation in pyod/models/hbos.py to understand current handling of features. Determine if categorical features are already handled implicitly or if a new parameter is needed. Review comments on this issue for any proposed solutions or workarounds. Implement a parameter 'categorical features' that accepts indices or column names, and adjust binning accordingly.