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This repo contains the ML model for the regression of calibrated FRED parameters

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FRED Parameters Prediction with ROCKET

This repository contains code for training a machine learning model using ROCKET and scikit-learn to predict the parameters of the FRED agent-based model. The FRED model simulates the spread of COVID and outputs various parameters related to the spread, including death reports.

Repository Description

This repository contains the following directories and files:

  • input_files: Contains input files required for the FRED simulation and the output files from the simulation, including FRED_parameters_out.csv and various data files related to different parameter variants.

  • scripts: Contains Python scripts and Jupyter notebooks for data processing, loading functions, and training the ROCKET model to predict FRED parameters.

Getting Started

To get started with this repository, follow these steps:

  1. Clone the repository:

    git clone https://github.com/your_username/fred-parameters-prediction.git
    
  2. Install the required dependencies. The dependencies can be found in the requirements.txt file. You can install them using pip:

    pip install -r requirements.txt
    
  3. Navigate to the scripts/ directory and run the Jupyter notebooks or Python scripts to preprocess the data and train the ROCKET model.

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This repo contains the ML model for the regression of calibrated FRED parameters

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