https://github.com/mubarak-mohamed/guessing-game
Guessing Game
https://github.com/mubarak-mohamed/guessing-game
ai machine-learning-algorithms pandas-dataframe python-library uci-machine-learning
Last synced: 10 months ago
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Guessing Game
- Host: GitHub
- URL: https://github.com/mubarak-mohamed/guessing-game
- Owner: mubarak-mohamed
- License: mit
- Created: 2025-05-02T22:23:45.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-04T22:40:47.000Z (about 1 year ago)
- Last Synced: 2025-05-17T20:11:23.094Z (about 1 year ago)
- Topics: ai, machine-learning-algorithms, pandas-dataframe, python-library, uci-machine-learning
- Language: Python
- Homepage:
- Size: 137 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Security: SECURITY.md
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README
[](https://github.com/mubarak-mohamed/guessing-game.git)
[](https://badge.fury.io/py/numpy)
jeu de la Devinette
# Table of content
- [Overview](#Overview)
- [Data format](#fData-format)
- [dataset](#dataset)
- [Citation](#Citation)
- [Features](#Features)
- [Licence](#licence)
# Overview
The project under consideration implements a guessing game in which the computer attempts to discern an animal or object that the user is contemplating by posing yes/no questions. The implementation utilizes a decision tree to efficiently narrow down the possibilities.
# Installation
1. Clone this repository :
```bash
git clone https://github.com/zool-techno/guessing-game.git
cd guessing-game
```
# Install the dependencies:
- Required packages (install using `pip install -r requirements.txt`) :
- Python 3.12 or higher
- pandas
- numpy
- scikit-learn
# Project structure :
- `main.py` : The primary game implementation and data pre-processing module
- `requirements.txt` : Project dependencies
- `assets/zoo.csv` : Example dataset
# Use
- Prepare your dataset. You can download it [here](https://archive.ics.uci.edu/dataset/111/zoo) in CSV format with the characteristics of the animals/objects.
2. Run the game :
```bash
python main.py
```
3. Follow the on-screen instructions to play.
# Data format
The dataset must be in CSV format with :
- One column per characteristic
- The last column must contain the name of the animal/object
- Values must be binary (0/1) for qualitative characteristics
- Numerical values will be normalised automatically
# dataset
| animal_name | hair | feathers | eggs | milk | airborne | aquatic | venomous | fins | legs | tail | domestic | catsize | type |
|-------------|------|----------|------|------|----------|--------|----------|------|------|------|----------|---------|------|
| aardvark | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 1 | 1 |
| antelope | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 | 1 | 0 | 1 | 1 |
| bass | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
| bear | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 1 | 1 |
| boar | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 |
# Citation
```tex
@online{noauthor_cours_nodate,
title = {Cours - Arbres de décision — Cnam – {UE} {RCP}209},
url = {https://cedric.cnam.fr/vertigo/cours/ml2/coursArbresDecision.html}
}
```
```
- Quinlan, J. R. (1986). Induction of decision trees. Machine learning, 1(1), 81-106.
- Breiman, L., Friedman, J., Stone, C. J., & Olshen, R. A. (1984). Classification and regression trees.
- McKinney, W. (2010). Data structures for statistical computing in python. Proceedings of the 9th Python in Science Conference, 51-56.
```
# Features
Potential improvements include:
- Adding sound effects and animations
- Implementing a more sophisticated learning mechanism
- Adding a graphical user interface
- Supporting multiple languages
# Licence
This project is under [MIT license](https://gitlab.com/mubarak-mohamed/guessing-game/-/blob/58271dc731aced70a640748f83b2752a0f4f90a1/LICENSE). See the LICENSE file for more details.
[](https://creativecommons.org/licenses/by-nc-sa/2.0/)