COMPARATIVE ANALYSIS OF GUI BASED HEALTH CARE DISEASE PREDICTION USING MACHINE LEARNING APPROACH
DOI:
https://doi.org/10.61841/scy2sm32Keywords:
dataset, Machine learning-Classification method, pythonAbstract
Commonly, viral and mosquito borne diseases rise seasonally and regionally. Hygiene is one of the motives why a few areas in India have higher sickness rate in comparison to others .It'd be fantastic if an application may want to collect data, analyze and report to authorities. To prevent this problem in medical sectors need to predict the alert fitness illnesses (like diabetes, continual, coronary heart assault) with the aid of signs the use of gadget studying strategies. The purpose is to research device learning based strategies for disease forecasting by means of prediction effects in high-quality accuracy. The analysis of dataset by using supervised gadget mastering approach(SMLT) to seize several statistics’s like, variable identification, uni-variate evaluation, bi-variate and multi-variate evaluation, missing value remedies and analyze the data validation.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
