Outlier Data Detection Systems - ODDS

As used in paper "Simple Models are Effective in Anomaly Detection in Multi-variate Time Series"

Contains an OD object

Instantiate the object with the 'algo' argument

eg. od = OD('VAR') instantiates an outlier detection system using vector autoregression

get outlier scores using the 'get_os()' function

eg. outlier_scores = od.get_os(X)

Where X is a data matrix, n samples by p features. P must be 2 or greater to work on many of the systems, this returns a vector with n scores, one for each sample.

Higher numbers mean more outlying.

Valid strings for outlier algorithms:

'VAR' vector autoregression
'FRO' ordinary feature regression
'FRL' LASSO feature regression
'FRR' Ridge feature regression
'GMM' Gaussian Mixture model
'IF' isolation Forest
'DBSCAN' Density Based Spatial clustering and noise
'OCSVM' one class support vector machine
'LSTM' long short term memory
'GRU' gated recurrent unit
'AE' autoencoder
'VAE' variational autoencoder
'OP' outlier pursuit
'GOP' graph regularised outlier pursuit
'RAND' random scoring (for baseline comparison)

Release files for odds 0.1.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for odds 0.1.3
File	Size	Uploaded
odds-0.1.3.tar.gz	5.6 kB	Nov 8, 2021	Details

Built distribution (wheel)

Table of built distributions (wheels) for odds 0.1.3
File	Interpreter	ABI	Platform	Reset
odds-0.1.3-py3-none-any.whl 2.7 kB Nov 8, 2021	Python 3	none	any	Details

Total release size: 8.4 kB

Release files / odds-0.1.3.tar.gz

Download URL	odds-0.1.3.tar.gz
Size	5.6 kB
Tags	Source
SHA-256 checksum How to use checksums	`3f987350a3950686a3b1ab9ec56d4aac0e95ccdcd7be9524a96fde3b3f265781`
BLAKE2b-256 checksum How to use checksums	`1a775e3b777eb61e13e97b670ea2e4d293983c21b13a117ee3b0355baa32edbb`
Upload date	Nov 8, 2021
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.5.0 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12`

Release files / odds-0.1.3-py3-none-any.whl

Download URL	odds-0.1.3-py3-none-any.whl
Size	2.7 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`b29ce00ecfd4e381ec641a937d79623b80833fac57fc6341a04025b7d5af9d8b`
BLAKE2b-256 checksum How to use checksums	`8868f5a8169634798b422d56f5908fa6cd4f01bce5f606cdf8b4c9c0810a0d19`
Upload date	Nov 8, 2021
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.5.0 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12`