Digital-Advertising-Conversion-Fraud
๐ Discription
- This Project is based on building a machine learning model to Detect the digital advertising conversion fraud.
- This project is implemented using Gradient Boosting Classifier
โณ Data Set
๐ฅ๏ธ Installation
๐ ๏ธ Requirements
- Programming Language: Python 3.5+
- Tools: Spyder IDE (or any other IDE)
- Libraries: Pandas, Numpy, Matplotlib, Seaborn, Scikit-learn
โ๏ธ Setup
- Python (https://www.python.org/downloads)
- Spyder IDE (https://www.spyder-ide.org)
- Libraries
pip install pandas
pip install numpy
pip install matplotlib
pip install seaborn
pip install scikit-learn
๐ Model
-
Gradient Boost Classifier
- Accuracy: 96.89%
- Cross-Validation: 96.66%
๐ License
Apache License 2.0