/Covid-19-Patient-Health-Analytics

A Boosted Random Forest Classification model was implemented to predict the outcome of the CoV-2 positive patients in China. Based on multiple features.

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Covid-19-Patient-Health-Analytics

A Boosted Random Forest Classification model was implemented to predict the outcome of the CoV-2 positive patients in China. Based on multiple features.

The original dataset was taken from: https://www.kaggle.com/sudalairajkumar/novel-corona-virus-2019-dataset

cvd

  • data.csv -> original dataset
  • train.csv -> training dataset (contains data for 'death' and 'recovered' columns)
  • test.xlsx -> test dataset (does not contains data for 'death' and 'recovered' columns)

final.csv -> result obtained by running the model on test.xlsx

Steps to reproduce results:

  1. Place the 'cvd' directory in your Google Drive.
  2. Connect the Colab Notebook to Google Drive.
  3. Run the 'Covid-19 Patient Health Prediction.ipynb' file.