# VFPRED codes

## Implementation

The entire alogrithm is implemented in Python3.

The functions are organized in the following files:

1) data_structures.py : All the data structures used in VFPred
2) data_handling.py : Downloading and processing the data
3) helper_function.py : Helper function
4) signal_processing.py : All the signal processing tasks
5) machine_learning.py :  All the machine learning tasks, including Random Forest, SMOTE , SVM

## Pipeline

The complete flow VFPred is presented in the Jupyter Notebook [VFPred.ipynb](https://github.com/nibtehaz/VFPred/blob/master/codes/VFPred.ipynb)

## Requirements

> * Numpy
> * Scipy
> * PyEMD
> * Scikit-learn
> * Imbalanced-learn
> * Pandas
> * wfdb
> * tqdm
> * Matplotlib
> * Seaborn


