Prediction-with-denoising

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.

Requirements

To run the project, you need to have the following installed on your machine:

1. Python 3.x
2. NumPy
3. Matplotlib
4. Scikit-learn All library that you need is imported in the file

Getting Started

To use the project, follow these steps:

1. Clone the repository to your local machine.
2. Install the required dependencies using the command pip install -r requirements.txt.
3. Run the PredictionWithDenoising.ipynb file.

Usage

The project consists of two main parts:

PredictionWithDenoising.ipynb: contains the implementation of the denoising algorithm. Nikkei.csv file that contains of data.

Contributing

If you would like to contribute to the project, please follow these steps:

1. Fork the repository.
2. Make your changes.
3. Submit a pull request.