Python implementation of SmartSifter
Project description
# SmartSifter
This is Python implementation of [SmartSifter - On-line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms (Yamanishi et al., 2004)](https://togaware.com/papers/kdd00.pdf).
## Install pip install smartsifter
## Usage See sample.py
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file smartsifter-0.1.1.dev1.tar.gz.
File metadata
- Download URL: smartsifter-0.1.1.dev1.tar.gz
- Upload date:
- Size: 2.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.6.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f112df81c4c3ee36ef47c953ea80dac2dc3526150565ad898d555b8344827d27
|
|
| MD5 |
8afee29bf8aad69f8a31e4d9ff225e0c
|
|
| BLAKE2b-256 |
127c586af32342a9a8327db9cd8964cb4452d3806dde690c242d629bb947b71a
|