Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/kelvin229/deap_genetic_programming
Using Genetic programming, an Evolutionary Algorithm, to solve and research the problem of Symbolic regression analysis and Rice Classification.
https://github.com/kelvin229/deap_genetic_programming
agricultural-modelling agricultural-technology agriculture-research deap deap-library evolutionary-algorithms genetic-programming machine-learning machine-learning-algorithms packages python rice-classification scientific-reports scientific-research symbolic-regression
Last synced: 7 days ago
JSON representation
Using Genetic programming, an Evolutionary Algorithm, to solve and research the problem of Symbolic regression analysis and Rice Classification.
- Host: GitHub
- URL: https://github.com/kelvin229/deap_genetic_programming
- Owner: Kelvin229
- Created: 2024-01-20T12:29:33.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-02-20T20:48:46.000Z (11 months ago)
- Last Synced: 2024-11-09T07:30:53.066Z (2 months ago)
- Topics: agricultural-modelling, agricultural-technology, agriculture-research, deap, deap-library, evolutionary-algorithms, genetic-programming, machine-learning, machine-learning-algorithms, packages, python, rice-classification, scientific-reports, scientific-research, symbolic-regression
- Language: Python
- Homepage:
- Size: 998 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# deap_genetic_programming
## Requirements
- Python
- Pip
## Usage
1. Install assignment packages
```sh
$ pip install -e packages/symreg packages/riceclf
```
2. Run the symbolic regression experiments
```sh
$ symreg
```
- For usage help:
```sh
$ symreg --help
```
3. Run the rice classification experiment.
- We can run the experiment using the following commands:
```sh
$ riceclf experiment -o tmp --seed 123 456 789 2974 2479 24755 74593 57993 24749 279
```
- Now give it some time for each (alot of time, go get a coffee or something... and come back to the program), to allow it to process until its all done.
- Then to plot the results, run the following command:
```sh
$ riceclf plot tmp/result.csv tmp/result.png
```
- Now check the `tmp` folder for the results in the root directory of the project.
4. For an individual run, create a folder `riceclf_output` using the following command:
```sh
$ mkdir riceclf_output
```
- Then run the following command to run the experiment and save the results to a file `riceclf_output/run123.csv`:
```sh
$ riceclf run -o riceclf_output/run123.csv --seed 123
```
- Then to plot the results, run the following command:
```sh
$ riceclf plot riceclf_output/run123.csv riceclf_output/run123.png
```
5. For usage help:
```sh
$ riceclf --help
$ riceclf run --help
$ riceclf experiment --help
$ riceclf plot --help
```
## References:
- F.-A. Fortin, F.-M. De Rainville, M.-A. Gardner, M. Parizeau, and C. Gagné, “DEAP: Evolutionary algorithms made easy,” Journal of Machine Learning Research, vol. 13, pp. 2171–2175, jul 2012. https://deap.readthedocs.io/en/master/
- Cinar, I. and Koklu, M. (2019). Classification of Rice Varieties Using Artificial Intelligence Methods. International Journal of Intelligent Systems and Applications in Engineering, vol.7, no.3 (Sep. 2019), pp.188-194. https://doi.org/10.18201/ijisae.2019355381.