Metadata-Version: 2.1
Name: mloptimizer
Version: 0.5.2
Summary: Genetic hyper-parameter selection for machine learning algorithms
Home-page: https://github.com/Caparrini/mloptimizer
Author: Antonio Caparrini
Author-email: a.caparrini@gmail.com
License: UNKNOWN
Description: # mloptimizer
        
        **mloptimizer** is a Python module for hyper-parameters optimization in machine learning using genetic algorithms.
        
        
        ### Installation
        
        ```bash
        pip install mloptimizer
        ```
        ### Quickstart
        
        A simple example of use optimizing hyper-parameters in a decision tree classifier using the iris dataset:
        
        ```python
        from mloptimizer.genoptimizer import TreeOptimizer
        from sklearn.datasets import load_iris
        
        X, y = load_iris(return_X_y=True)
        opt = TreeOptimizer(X, y, "output_log_file.log")
        clf = opt.optimize_clf(10, 10)
        ```
        
        ## Modules used
        
        * [Deap](https://github.com/DEAP/deap) - Genetic Algorithms
        * [XGBoost](https://github.com/dmlc/xgboost) - Gradient boosting classifier
        * [sklearn](https://github.com/scikit-learn/scikit-learn) - Usado para generar RSS
        
        ## Wiki
        
         TODO [Wiki](DOCUMENTATION TODO)
        
        ## Authors
        
        * **Antonio Caparrini** - *Owner* - [caparrini](https://github.com/caparrini)
        
        ## License
        
        This project is under the [LICENSE](LICENSE) for more details.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
