Romain Egele

Hello, I propose a tiny edit to the documentation, where I noticed that the `priv_group` parameter is documented in `sklearn.metrics.average_odds_error` but not accessible. Best.

Leveraging the "category" type from pandas for Categorical-Ordinal

2

### Problem Description Hello, if I understood the API correctly. Dimensions are either "real", "discrete" or "categorical" and this is automatically inferred based on the `dtype` of each column. For...

Implement a lightweight DBManager based on TinyDB. - [x] hyperparameter search - [ ] neural architecture search - [ ] [documentation API](https://deephyper.readthedocs.io/en/develop/_autosummary/deephyper.core.analytics.DBManager.html) - [ ] example usage documentation

## Experiment selection We could use Pyparsing: https://pyparsing-docs.readthedocs.io/en/latest/HowToUsePyparsing.html#using-the-pyparsing-module to have a search based on a query ## Single experiment analysis - [x] scatter plot - [x] display CSV file -...

[Link to the page to edit](https://github.com/deephyper/deephyper/blob/develop/docs/user_guides/data_parallelism.rst) - [x] HPS case with Balsam, MPI, and Horovod - [ ] HPS case with Ray and Tensorflow distributed - [ ] NAS case...

[Link to the page to edit](https://github.com/deephyper/deephyper/blob/develop/docs/user_guides/nas/stacked_lstm.rst) - [ ] describe the geophysical use case (SC20) - [ ] describe the stacked LSTM search space - [ ] shows a figure...

[Link to the page to edit](https://github.com/deephyper/deephyper/blob/develop/docs/user_guides/nas/graphnn.rst) Take inspiration from the [Graph NN repo](https://github.com/deephyper/nas-gcn) - [ ] transfer [tutorial](https://github.com/deephyper/nas-gcn/blob/master/nas_gcn/nas_gcn_tutorial.rst) provided by Bruce - [ ] add test script

[Link to the page to edit](https://github.com/deephyper/deephyper/blob/develop/docs/user_guides/nas/convolutions.rst) Take inspiration from the [CIFAR10 case](https://github.com/deephyper/nas-ensemble/tree/main/nas_ensemble/cifar10)

[Link to the page to edit](https://github.com/deephyper/deephyper/blob/develop/docs/user_guides/nas/tabular_data.rst) Take inspiration from the [AgEBO-Tabular repo](https://github.com/deephyper/NASBigData)

[Link to the page to edit](https://github.com/deephyper/deephyper/blob/develop/docs/user_guides/nas/autoencoder.rst)