https://github.com/ilovenooodles/convex-hull-implementation
Tugas Kecil 2 Strategi Algoritma: Convex Hull Implementation for Linear Separability Dataset Test with Divide and Conquer
https://github.com/ilovenooodles/convex-hull-implementation
convex-hull-algorithms dataset linear-separability python
Last synced: about 2 months ago
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Tugas Kecil 2 Strategi Algoritma: Convex Hull Implementation for Linear Separability Dataset Test with Divide and Conquer
- Host: GitHub
- URL: https://github.com/ilovenooodles/convex-hull-implementation
- Owner: IloveNooodles
- Created: 2022-02-21T07:34:27.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2022-02-27T10:14:35.000Z (about 3 years ago)
- Last Synced: 2025-02-06T08:44:40.435Z (3 months ago)
- Topics: convex-hull-algorithms, dataset, linear-separability, python
- Language: Python
- Homepage:
- Size: 8.79 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Convex Hull Visualization
This project is made to fulfill the 2nd project for the Strategic Algorithm. It is an Convex Hull Visualizer that can be used to visualize **Linear Separability** from the dataset given or sklearn dataset. This visualization made using python and using the principles of divide and conqueror algorithm.
## Screenshots
## Technologies Used
1. Python (3.8+)
2. NumPy
3. sklearn datasets
4. matplotlib
5. pandas
## Features
This program allows you to visualize **Linear Separability** test from 2 selected columns from dataset and must have **dataset classification** model in order to work. It will show you all the point from selected columns, legends, and the convex hull using matplotlib.
## Setup
1. Install all the requirements in the technologies section
2. If you want to use your dataset, you must put the dataset in test folder
3. Clone the github using `git clone https://github.com/IloveNooodles/convex-hull-implementation.git` or simply using download as zip file from the github
4. After that go to the folder directory
5. Run the program using `python main.py`
## Usage
1. After you run the program, you can choose the dataset you want to visualize.
2. Select either from the test folder or sklearn dataset
3. Your dataset must categorized as **dataset classification** and have **Target** column in order to work.
4. Select two columns that you want to visualize.
5. Ta-da! the matplotlib will show and you have your dataset visualization.
Note: If you input wrong dataset or input the program will prompt message and exit
## Room for Improvement
Maybe we can deploy this to a website for ease of use
## References
---
1. [Convex hull](https://en.wikipedia.org/wiki/Convex_hull)
2. [Quickhull Algorithm]()
3. [Pandas](https://pandas.pydata.org/docs/)
4. [Visualization](https://matplotlib.org/)
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