https://github.com/abideen-olawuwo/healthmonitor

A model for healthmonitor
https://github.com/abideen-olawuwo/healthmonitor

knearest-neighbor-classifier logistic-regression matplotlib numpy pandas python random-forest-classifier seaborn sklearn

Last synced: 3 months ago
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A model for healthmonitor

• Host: GitHub
• URL: https://github.com/abideen-olawuwo/healthmonitor
• Owner: abideen-olawuwo
• Created: 2023-05-05T18:00:03.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2023-05-29T20:36:40.000Z (almost 2 years ago)
• Last Synced: 2025-01-15T05:40:12.023Z (4 months ago)
• Topics: knearest-neighbor-classifier, logistic-regression, matplotlib, numpy, pandas, python, random-forest-classifier, seaborn, sklearn
• Language: Jupyter Notebook
• Homepage:
• Size: 1.77 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
* Problem Definition

Building classification models to predict whether patient disease is Chronic, Severe, Mild, Normal 

* Data

The data was downloaded from kaggle[https://www.kaggle.com/datasets/nraobommela/health-monitoring-system]

* Evaluation

The Evaluation metric is to get the best accuracy

* Features

The data Features include; 

Dehydration,	Medicine Overdose,	Acidious,	Cold,	Cough,	Dehydration,	Medicine Overdose, 

Acidious,	Cold,	Cough,	Type,	Temperature,	Heart Rate,	Pulse,	

BPSYS,	BPDIA,	Respiratory Rate,	Oxygen Saturation.	PH

* Modelling

The Model used are Random Forest Classifier (RFC), Logistic Regression, Kneigbhor