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...
- ...
- ...
- ...
-
...
took an estimated 1 years of effort (COCOMO model)
starting with its first commit in August, 2014
ending with its most recent commit over 2 years ago
Quick Reference
GNU General Public License v2.0 or later
Permitted
Commercial Use
Modify
Distribute
Place Warranty
Forbidden
Sub-License
Hold Liable
Required
Distribute Original
Disclose Source
Include Copyright
State Changes
Include License
These details are provided for information only. No information here is legal advice and should not be used as such.
Project Security
Vulnerabilities per Version ( last 10 releases )
There are no reported vulnerabilities
Project Vulnerability Report
Security Confidence Index
Vulnerability Exposure Index
Did You Know...
-
...
there are over 3,000 projects on the Open Hub with security vulnerabilities reported against them
-
...
compare projects before you chose one to use
-
...
55% of companies leverage OSS for production infrastructure
-
...
learn about Open Hub updates and features on the Open Hub blog
30 Day SummaryMar 24 2024 — Apr 23 2024
|
12 Month SummaryApr 23 2023 — Apr 23 2024
|
