https://github.com/eug/hysortod.py

Fast and Scalable Outlier Detection with Sorted Hypercubes
https://github.com/eug/hysortod.py

detection neighborhood outlier scalable unsupervised-learning

Last synced: 5 months ago
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Fast and Scalable Outlier Detection with Sorted Hypercubes

• Host: GitHub
• URL: https://github.com/eug/hysortod.py
• Owner: eug
• License: apache-2.0
• Created: 2020-08-11T01:59:47.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2021-02-18T22:19:46.000Z (over 5 years ago)
• Last Synced: 2025-09-21T01:44:07.589Z (9 months ago)
• Topics: detection, neighborhood, outlier, scalable, unsupervised-learning
• Language: Python
• Homepage:
• Size: 59.1 MB
• Stars: 3
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# HySortOD

[![Downloads](https://pepy.tech/badge/hysortod)](https://pepy.tech/project/hysortod) [![DOI:10.1145/3340531.3412033](https://zenodo.org/badge/DOI/10.1145/3340531.3412033.svg)](https://doi.org/10.1145/3340531.3412033) [![PyPI version fury.io](https://badge.fury.io/py/hysortod.svg)](https://pypi.python.org/pypi/hysortod) 



    



Outlier Detection with Sorted Hypercubes. Java version is available in hysortod.java.

### Install

```sh

pip install hysortod

```

### Example

```python

import pandas as pd

from hysortod import HySortOD

df = pd.read_csv("datasets/breastw.csv")

X = df.drop(columns='class')

y = df['class']

hysortod = HySortOD()

hysortod.fit(X)

print(hysortod.score(X, y))

```

### Reference

Eugenio F. Cabral and Robson L. F. Cordeiro. 2020. Fast and Scalable Outlier Detection with Sorted Hypercubes. In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM'20), October 19–23, 2020. Virtual Event, Ireland. ACM, New York, NY, USA, 10 pages.