Name | PyDataforge JSON |
Version |
1.0.9
JSON |
| download |
home_page | None |
Summary | None |
upload_time | 2024-08-10 07:10:52 |
maintainer | None |
docs_url | None |
author | Guipeng Wei |
requires_python | None |
license | MIT License |
keywords |
|
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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This is a package for removing sensitive information from data, which utilizes automatic encoder, one-dimensional convolutional layer and bidirectional generative adversarial network to build a model to generate high-quality data.
It provides:
- efficient feature extraction using multi-layer convolution
- novel bidirectional generative adversarial network
- secure sensitive information protection mechanism
- high-quality data generation for practical applications
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