patternly 0.0.19

A tool for detecting anomalies in time series data

Info:

Paper draft link will be posted here

Author:

Drew Vlasnik, Ishanu Chattopadhyay

Laboratory:

The Laboratory for Zero Knowledge Discovery, The University of Chicago https://zed.uchicago.edu

Description:

Discovery of emergent anomalies in data streams without explicit prior models of correct or aberrant behavior, based on the modeling of ergodic, quasi-stationary finite valued processes as probabilistic finite state automata (PFSA).

Documentation:

https://zeroknowledgediscovery.github.io/patternly

Installation:

pip install patternly --user -U

Usage:

See examples.

from patternly.detection import AnomalyDetection