IntelELM: A Python Framework for Intelligent Metaheuristic-based Extreme Learning Machine
IntelELM (Intelligent Metaheuristic-based Extreme Learning Machine) is a Python library that implements a framework for training Extreme Learning Machine (ELM) networks using Metaheuristic Algorithms. It provides a comparable alternative to the traditional ELM network and is compatible with the Scikit-Learn library. With IntelELM, you can perform searches and hyperparameter tuning using the functionalities provided by the Scikit-Learn library.
- Free software: GNU General Public License (GPL) V3 license
- Provided Estimator: ElmRegressor, ElmClassifier, MhaElmRegressor, MhaElmClassifier
- Total Optimization-based ELM Regression: > 200 Models
- Total Optimization-based ELM Classification: > 200 Models
- Supported datasets: 54 (47 classifications and 7 regressions)
- Supported performance metrics: >= 67 (47 regressions and 20 classifications)
- Supported objective functions (as fitness functions or loss functions): >= 67 (47 regressions and 20 classifications)
- Documentation: https://intelelm.readthedocs.io/en/latest/
- Python versions: >= 3.7.x
- Dependencies: numpy, scipy, scikit-learn, pandas, mealpy, permetrics
.. toctree:: :maxdepth: 4 :caption: Quick Start: pages/quick_start.rst
.. toctree:: :maxdepth: 4 :caption: Models API: pages/intelelm.rst
.. toctree:: :maxdepth: 4 :caption: Support: pages/support.rst