Name | diresa JSON |
Version |
1.0.6
JSON |
| download |
home_page | |
Summary | Diresa - distance-regularized siamese twin autoencoder |
upload_time | 2024-02-18 18:21:27 |
maintainer | |
docs_url | None |
author | |
requires_python | >=3.6 |
license | |
keywords |
climate
learning
machine
tensorflow
weather
|
VCS |
|
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
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coveralls test coverage |
No coveralls.
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# *DIRESA*
### Overview
*DIRESA* is a Python package for dimension reduction based on
[TensorFlow](https://www.tensorflow.org). The distance-regularized
Siamese twin autoencoder architecture is designed to preserve distance
(ordering) in latent space while capturing the non-linearities in
the datasets.
### Prerequisites
The *DIRESA* package depends on the [tensorflow](https://www.tensorflow.org)
and [tensorflow_probability](https://www.tensorflow.org/probability) packages.
These can be installed with the following commands:
``` bash
pip install tensorflow
pip install tensorflow_probability
```
### Install *DIRESA*
Install *DIRESA* with the following command:
``` bash
pip install diresa
```
### Documentation
The *DIRESA* documentation can be found on [Read the Docs](https://diresa-learn.readthedocs.io)
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