Metadata-Version: 2.4
Name: PyTSML
Version: 1.0
Summary: Placeholder
Project-URL: Homepage, https://github.com/Bl0tniaQus/PyTSML
Project-URL: Issues, https://github.com/Bl0tniaQus/PyTSML/issues
Author-email: Adrian Hałys <bl0tniaqus578@gmail.com>
License-Expression: Apache-2.0
License-File: LICENSE
Keywords: Classification,DDE,DE,DTW,Delay Embedding,LDMLT,Machine Learning,Time Series
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.11
Requires-Dist: fastdtw>=0.3.4
Requires-Dist: scipy>=1.14.1
Description-Content-Type: text/markdown

# PyTSML
## Python Time Series Machine Learning

This package, which was initially made as a result of my MSC Thesis in Computer Engineering, contains Python implementations of few machine learning algorithms designed to work (mainly classify) data in the time series format.

### Currently implemented methods:

- LDMLT (LogDet Divergence-Based Metric Learning With Triplet Constraints) [Mei, J., Liu, M., Karimi, H.R., & Gao, H. (2014). LogDet Divergence-Based Metric Learning With Triplet Constraints and Its Applications. IEEE Transactions on Image Processing, 23, 4920-4931.];
- DDE (Derivative Delay Embedding) [Zhang, Z., Song, Y., Wang, W., & Qi, H. (2016). Derivative Delay Embedding: Online Modeling of Streaming Time Series. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management.];
- KNN classifier with DTW distance.

# Usage
To use the package, build the wheel yourself, install it through pip or just use the source file in Your project.

```
pip3 install PyTSML
```

# Contact

Please use Github issues page for anything related to this package.


