This project provides a Deep Learning algorithm for classifying forest cover types using the Covertype dataset. The model is a Bidirectional GRU, and the algorithm includes data preprocessing, hyperparameter tuning, model training, and evaluation.
The repository includes the following Python scripts.
├── dataset.py # Data loading and preprocessing
├── model.py # GRU model creation
├── train.py # Hyperparameter tuning and training logic
├── evaluate.py # Model evaluation and report generation
├── main.py # Entry point for the program
└── README.md # Instructions to run the project
Python 3.7 or higher
- Clone the repository:
git clone https://github.com/krishnapratap07/Cover_Type_Project_GRU.git cd Cover_Type_Project_GRU - Install the required python package
pip install -r requirements.txt
Once the installation is complete, you can run the main program that will train the model and evaluate the results. To execute the script, run the following command in your terminal.
python main.py