shapes-from-time
Time series classification using Shapelets as proposed by Eamonn Keogh and Lexiang Ye. Shapelets are time series subsequences which are in some sense maximally representative of a class.
Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
Prerequisites
Following packages should be installed in your system before shapeletpy installation.
'markdown',
'collections',
'itertools',
'operator',
'pickle',
'random',
'threading',
'time',
'sklearn',
'matplotlib',
'numpy',
'pandas',
'progressbar',
'seaborn',
'saxpy',
'scipy'
Installing
For a fresh installation, run the below code:
pip install shapeletpy
If you need to reinstall the existing copy of this package, execute the following command:
pip install --upgrade --force-reinstall shapeletpy
You should get an output as shown below:
Installing collected packages: shapeletpy Found existing installation: shapeletpy 0.1 Successfully installed shapeletpy-0.1
Running the tests
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And coding style tests
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Deployment
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Built With
- Dropwizard - The web framework used
- Maven - Dependency Management
- ROME - Used to generate RSS Feeds
Contributing
Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.
Versioning
We use SemVer for versioning. For the versions available, see the tags on this repository.
Authors
- Rohit Vincent - Initial work - rohitvincent
See also the list of contributors who participated in this project.
License
This project is licensed under the MIT License - see the LICENSE.md file for details
Acknowledgments
- Hat tip to anyone whose code was used
- Inspiration
- etc