jMotif

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Very Low Activity

Analyzed about 19 hours ago. based on code collected 2 days ago.

Project Summary

JMotif implements in Java number of methods for timeseries data handling and analysis:
* Z normalization of timeseries
* Piecewise Aggregate Approximation (PAA) of timeseries
* Symbolic Aggregate Approximation (SAX) of timeseries
* iSAX (indexed SAX)

in order to help one leverage the symbolic representation of timeseries, it implements:
* TFIDF statistics
* Cosine similarity
* Sequitur algorithm

as well as their application for:
* Motif (recurring patterns) detection with SAX
* Discord (unique patterns) detection with SAX
* Timeseries classification
* Timeseries clustering

Badges

In a Nutshell, jMotif...

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has had 294 commits made by 2 contributors
representing 5,271 lines of code
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is mostly written in Java
with an average number of source code comments
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has a well established, mature codebase
maintained by one developer
with increasing Y-O-Y commits
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took an estimated 2 years of effort (COCOMO model)
starting with its first commit in August, 2014
ending with its most recent commit about 2 months ago

Quick Reference

Project Links:

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Code Locations:

https://github.com/jMotif/sax-vs...

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Managers:

Pavel Senin

Licenses

GNU General Public License v2.0 or later

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These details are provided for information only. No information here is legal advice and should not be used as such.

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Project Security

Vulnerabilities per Version ( last 10 releases )

There are no reported vulnerabilities

Project Vulnerability Report

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Poor security track-record

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Vulnerability Exposure Index

Many reported vulnerabilities

Few reported vulnerabilities

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