ALICE - Automated Labeling of Independent Components for EEG
The project aims to develop a sustainable algorithm for EEG IC artifact removal and collect a publically available dataset.
Read about out project in the recent publication
alice-ml library contains pretrained ML models to label IC. It's compatible with MNE library.
Requirements
- Python >= 3.7
Installation
Currently only pip installation is supported
pip install alice-ml
1 maintainer
Release files for alice-ml 0.3.9
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| alice-ml-0.3.9.tar.gz | 7.0 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| alice_ml-0.3.9-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 14.1 MB
Release files / alice-ml-0.3.9.tar.gz
| Download URL | alice-ml-0.3.9.tar.gz |
|---|---|
| Size | 7.0 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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No |
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twine/4.0.1 CPython/3.7.1
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Release files / alice_ml-0.3.9-py3-none-any.whl
| Download URL | alice_ml-0.3.9-py3-none-any.whl |
|---|---|
| Size | 7.0 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.7.1
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