This project focuses on understanding knowledge extraction methods using RStudio. Data exploration and analysis are crucial steps in any machine learning project. In this task, we work with the Zoo database, containing information about various animals in a zoo. The objective is to extract knowledge from this data using different techniques, including:
- Association Rules
- Hierarchical Agglomerative Clustering (HAC)
- K-means Clustering
- Decision Trees
- Data Science
- Data Mining
- Clustering
- Data Visualization
- Data Analysis
- K-means
- Decision Trees
- Association Rules
- Hierarchical Clustering
- R Programming
- R Studio
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Clone the repository:
git clone https://github.com/walidbosso/R_Data_mining.git
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Explore the individual project files (
1-Exportation_Arbre_Clustering.Rand2-AR.R) for code and resources. -
Make sure you have RStudio installed and configured.
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Run the R scripts within your RStudio environment.
This project is licensed under the MIT License - see the LICENSE file for details.
If you'd like to contribute to the project, please follow these steps:
- Fork the repository.
- Create a new branch (
git checkout -b feature/your-feature). - Commit your changes (
git commit -m 'Add some feature'). - Push to the branch (
git push origin feature/your-feature). - Open a pull request.
If you encounter any issues or have suggestions, please open an issue on the Issues page.
Thank you for exploring the R Data Mining project! 🚀
