This project is a demonstration of how denoising can improve the accuracy of predictive models. The main objective of the project is to provide a simple and easily understandable implementation of denoising with kalman filter in the context of predictive modeling.
To run the project, you need to have the following installed on your machine:
- Python 3.x
- NumPy
- Matplotlib
- Scikit-learn All library that you need is imported in the file
To use the project, follow these steps:
- Clone the repository to your local machine.
- Install the required dependencies using the command pip install -r requirements.txt.
- Run the PredictionWithDenoising.ipynb file.
The project consists of two main parts:
PredictionWithDenoising.ipynb: contains the implementation of the denoising algorithm. Nikkei.csv file that contains of data.
If you would like to contribute to the project, please follow these steps:
- Fork the repository.
- Make your changes.
- Submit a pull request.