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https://github.com/gz30eee/dm
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- Host: GitHub
- URL: https://github.com/gz30eee/dm
- Owner: GZ30eee
- Created: 2024-12-21T17:04:56.000Z (about 1 month ago)
- Default Branch: master
- Last Pushed: 2024-12-21T17:07:19.000Z (about 1 month ago)
- Last Synced: 2024-12-21T18:20:17.705Z (about 1 month ago)
- Language: Python
- Size: 5.48 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Data Mining Projects
This repository contains a collection of data mining projects demonstrating various techniques such as association rule mining, clustering, sentiment analysis, and more. Below is a list of the projects included in this repository:
---
### **Projects Overview**
#### **Apriori Algorithm**
- `main.py`
An implementation of the Apriori algorithm for mining frequent itemsets and generating association rules.
#### **Association Rule Generator**
- `ap.py`
A tool that generates association rules based on the results from the Apriori algorithm.
#### **Binning Methods**
- `bin.py`
A project demonstrating various binning techniques to discretize continuous data into discrete bins.
#### **Clustering Visualization**
- `clu.py`
A project that visualizes the clustering of data using K-Means and other clustering algorithms.
#### **Movie Recommendation System**
- `movie.py`
A recommendation system for movies based on collaborative filtering or content-based methods.
#### **Sentiment Analysis**
- `sen.py`
- `cleaned_data.csv`
- `tweets.csv`
A project to perform sentiment analysis on tweets and other textual data using the TextBlob library.
#### **Stock Price Estimation**
- `f.py`
A tool to estimate and predict stock prices using historical data and the Yahoo Finance API.
---
## **Getting Started**
### **Step 1: Clone the Repository**
Clone this repository to your local machine by running the following command:
```bash
git clone https://github.com/GZ30eee/DM.git
cd DM
```
---
### **Step 2: Install Required Libraries**
These projects require several external libraries. To install them, run the following command:
```bash
pip install -r requirements.txt
```
Alternatively, you can manually install the required libraries by running:
```bash
pip install tkinter pandas mlxtend yfinance matplotlib textblob numpy scikit-learn requests beautifulsoup4
```
---
## **Running the Projects**
Each project can be executed independently. You can run the scripts in the following way:
```bash
python main.py
python ap.py
python bin.py
python clu.py
python movie.py
python sen.py
python f.py
```
For projects involving datasets like `cleaned_data.csv` or `tweets.csv`, ensure the data files are in the same directory or adjust the file paths in the code accordingly.
---
## **Contributing**
Feel free to fork this repository, make your changes, and submit a pull request. Contributions are welcome!
---
## **License**
This repository is open-source and available under the MIT License.
---