heart-failure-prediction

Research Project Heart Failure Prediction

https://github.com/ananya2003gupta/heart-failure-prediction

Science Score: 44.0%

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  • CITATION.cff file
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    Low similarity (3.9%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Research Project Heart Failure Prediction

Basic Info
  • Host: GitHub
  • Owner: Ananya2003Gupta
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 5 MB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 3 years ago · Last pushed over 3 years ago
Metadata Files
Readme Citation

README.md

Heart-Failure-Prediction

This research project aims to improve the accuracy of heart failure prediction models using hyperparameter optimization and feature selection. 8 supervised learning classification algorithms namely Logistic Regression, KNN, Naive Bayes, SVM, Decision Tree, Random Forest, LightGBM and XGBoost predictions were analyzed and improved upon using hyperparameter optimization and feature selection. An accuracy of 87.83% was achieved using Random Forest for all 12 features and KNN for top 5 features (selected after feature selection).

Citation

To cite this repository refer to CITATION.cff

Owner

  • Name: Ananya Gupta
  • Login: Ananya2003Gupta
  • Kind: user

A tech geek who is trying and testing different programming languages, frameworks as well as technologies and playing around with them to create something new.

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: Heart Failure Prediction
message: >-
  If you use this software, please cite it using the 
  metadata from this file.
type: software
authors:
  - given-names: Ananya
    family-names: Gupta
    email: ananya004btcse21@igdtuw.ac.in
  - given-names: Astha
    family-names: Varshney
    email: astha119btcse21@igdtuw.ac.in
repository-code: >-
  https://github.com/Ananya2003Gupta/Heart-Failure-Prediction
date-released: '2022-08-29'

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