Metadata-Version: 2.1
Name: permetrics
Version: 1.0.0
Summary: A framework of PERformance METRICS (PerMetrics) for artificial intelligence models
Home-page: https://github.com/thieunguyen5991/permetrics
Author: Thieu Nguyen
Author-email: nguyenthieu2102@gmail.com
License: MIT
Download-URL: https://github.com/thieunguyen5991/permetrics/archive/v1.0.0.zip
Description: # Optimization Function in Numpy (OpFuNu)
        [![GitHub release](https://img.shields.io/badge/release-1.0.0-yellow.svg)]()
        [![Wheel](https://img.shields.io/pypi/wheel/gensim.svg)](https://pypi.python.org/pypi/permetrics) 
        [![PyPI version](https://badge.fury.io/py/permetrics.svg)](https://badge.fury.io/py/permetrics)
        [![DOI version](https://zenodo.org/badge/DOI/10.5281/zenodo.3620960.svg)](https://badge.fury.io/py/permetrics)
        [![License](https://img.shields.io/packagist/l/doctrine/orm.svg)]()
        
        ## Installation
        
        Install the [current PyPI release](https://pypi.python.org/pypi/permetrics):
        
        ```bash
        pip install permetrics
        ```
        
        Or install the development version from GitHub:
        
        ```bash
        pip install git+https://github.com/thieunguyen5991/permetrics
        ```
        
        
        ## Example
        + All you need to do is: (Make sure your solution is a numpy 1-D array)
        
        ```python 
        
        ## CEC-2013 (2 ways to use depend on your purpose)
        
        import numpy as np
        from opfunu.cec.cec2013.unconstraint import Model as M13
        from opfunu.cec.cec2014.unconstraint2 import Model as MD2
        
        problem_size = 10
        solution = np.random.uniform(0, 1, problem_size)
        
        
        obj = MD2(problem_size)             # Object style solve different problems with different functions
        print(obj.F1(solution))
        print(obj.F2(solution))
        
        obj = M13(solution)                 # Object style solve same problem with every functions
        print(obj.F1())
        print(obj.F2())
        
        ...
        ```
        
        ## References
        
        #### Publications
        + If you see my code and data useful and use it, please cites my works here
        ```code 
        @software{thieu_nguyen_2020_3711682,
          author       = {Thieu Nguyen},
          title        = {A framework of un-constrained Optimization Functions in Numpy (OpFuNu) for global optimization
         problems},
          month        = march,
          year         = 2020,
          publisher    = {Zenodo},
          doi          = {10.5281/zenodo.3620960},
          url          = {https://doi.org/10.5281/zenodo.3620960.}
        }
        
        @article{nguyen2019efficient,
          title={Efficient Time-Series Forecasting Using Neural Network and Opposition-Based Coral Reefs Optimization},
          author={Nguyen, Thieu and Nguyen, Tu and Nguyen, Binh Minh and Nguyen, Giang},
          journal={International Journal of Computational Intelligence Systems},
          volume={12},
          number={2},
          pages={1144--1161},
          year={2019},
          publisher={Atlantis Press}
        }
        ```
         
        + This project related to my another projects which are "meta-heuristics" and "neural-network", check it here
            + https://github.com/thieunguyen5991/metaheuristics
            + https://github.com/chasebk
        
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: System :: Benchmark
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.7
Description-Content-Type: text/markdown
