Skip to content

Fast and Scalable Outlier Detection with Sorted Hypercubes

License

Notifications You must be signed in to change notification settings

eug/hysortod.py

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

HySortOD

Downloads DOI:10.1145/3340531.3412033 PyPI version fury.io

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

Install

pip install hysortod

Example

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.