shubham-attri / fraud_detection-modelv1.0.0

AI model to evaluate transactions over a network

Fraud Detection using Linear Regression

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.

Dependencies

Python 3.9
NumPy
pandas
scikit-learn
Usage
matplotlib
sklearn
seaborn

To use the model, follow these steps:

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.

Evaluation

The model is evaluated using standard evaluation metrics such as accuracy, precision, and recall.

Screen Shot

License

Read the License.md for complete overview.

Credits

This project was developed by Shubham Attri