Auto-sklearn

using Bayesian optimization, and builds ensembles for classification and regression tasks.

Auto-sklearn simplifies the creation of accurate machine learning pipelines by automating data

preprocessing, model selection, evaluation, and optimization with minimal user intervention.

Features of Auto-sklearn:

• Automates model selection and hyperparameter tuning for supervised learning tasks.
• Supports both classification and regression problems.
• Handles preprocessing tasks such as missing value imputation, scaling, and encoding.
• Performs cross-validation and provides reliable performance metrics.
• Builds ensemble models to improve prediction accuracy and robustness.
• Supports parallel computation for faster and efficient model optimization.

Auto-sklearn Usage

$ sudo su

$ python3.9 -m venv autosklearn-env

$ source autosklearn-env/bin/activate

$ pip show auto-sklearn | grep Version

Disclaimer: Auto-sklearn is open-source software distributed under the BSD License. It is provided

"as is," without any warranty, express or implied. Users are responsible for proper installation, configuration,

and usage. The developers and contributors are not liable for any damages, losses, or consequences resulting

from its use. Users should comply with applicable licensing and regulatory requirements.