Auto-PyTorch vs auto-sklearn
Auto-PyTorch
automl.github.ioauto-sklearn
automl.github.ioSide by side
| Figure | Auto-PyTorch | auto-sklearn |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Linux | Yes | Yes |
| API | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · AutoML Software | 8.4 (#5) | 7.8 (#12) |
| Maker | The GitHub project says Auto-PyTorch is developed by the AutoML Groups of the University of Freiburg and Hannover. | The AutoML website identifies AutoML as a project of the Chair for Machine Learning at the University of Freiburg. |
| What it does | Auto-PyTorch is an automated machine-learning toolkit based on PyTorch that helps users automate algorithm selection and hyperparameter tuning. | auto-sklearn automates machine learning model fitting and ensemble construction for classification and regression tasks. |
Plans
In their own words
Auto-PyTorch
Auto-PyTorch is a free, self-hosted machine-learning toolkit based on PyTorch. It automates algorithm selection and hyperparameter tuning, including neural-network architecture and training settings, within a user-defined search budget. Documented search methods include Bayesian optimisation, meta-learning, SMAC and Hyperband. Supported work includes tabular classification, tabular regression and time-series forecasting. Tabular preprocessing can perform imputation, categorical encoding, scaling and feature processing, while related hyperparameters are tuned. The toolkit can build ensembles from validation-set predictions, with controls for ensemble size and candidate limits. Users can set estimator memory limits and total wall time. Parallel Bayesian optimisation uses Dask.distributed; workers need shared filesystem access to training data and models. Installation documentation specifies Linux, Python 3.7 or later, a C++11-capable compiler and SWIG 3.0. SWIG 4.0 or later is unsupported. Forecasting needs extra dependencies. A Docker image and PyPI installation are documented, under the 3-clause BSD license.
auto-sklearn
auto-sklearn has no write-up on Specifiction yet; its figures are above.