Preset Configurations#
This module contains preset configurations for baseline architectures and datasets.
Models#
Pytorch Models#
|
Chambon2018. |
|
Chambon2018. |
|
Hybrid sleep staging architecture composed of Chambon model and lstm layer parameters. |
|
Baseline LSTM layer model. |
|
Chambon2018. |
|
Hybrid sleep staging architecture composed of Chambon model and lstm layer parameters. |
|
Nine-layers-CNN. |
Scikit-learn Models (with grid-search)#
Datasets#
Datasets include iterative accessors to raw data (Supported Datasets) including data pre-processing and augmentation, if applicable. Use these datasets for training and evaluating your models.
Sleep-EDF (expanded) dataset for sleep analysis. |
|
Sleep-EDF (expanded) dataset for sleep analysis. |
|
Sleep-EDF (expanded) dataset for sleep analysis. |
|
Sleep-EDF (expanded) dataset for sleep analysis. |
|
Sleep-EDF (expanded) dataset for sleep analysis. |
|
Cross subset protocols: |
|
Cross subset protocols: |
|
Cross subset protocols: |
|
Montreal Archive of Sleep Studies (MASS) |
|
Montreal Archive of Sleep Studies (MASS) |
|
Cross dataset protocols: |
|
Cross dataset protocols: |
|
Cross dataset protocols: |
|
|
Cross dataset protocols: |
Cross dataset protocols: |
|
Cross dataset protocols: |