This repository contains a Python implementation of a machine learning model using linear regression to detect fraud in transactions over a network. The model is trained on a dataset of transactions, and can be used to predict whether a given transaction is fraudulent or not.
Python 3.9
NumPy
pandas
scikit-learn
Usage
matplotlib
sklearn
seaborn
Clone this repository: git clone https://github.com/shubham-attri/fraud-detection.git
Navigate to the repository directory: cd fraud-detection
Install the dependencies
Run the script: python fraud_detection.py
Dataset
The model is trained on a dataset of transactions that includes features such as the amount of the transaction, the time of the transaction, and the location of the transaction. The dataset also includes a label indicating whether the transaction is fraudulent or not.
The model is evaluated using standard evaluation metrics such as accuracy, precision, and recall.
Read the License.md for complete overview.
This project was developed by Shubham Attri