Identification of Brain Stroke using Boosted Random Forest-Reference-Cited by-同舟云学术

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Identification of Brain Stroke using Boosted Random Forest

Published:2022-11-10 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Advances in Computing, Communication and Materials (ICACCM)
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Author:

Sapra Varun¹,Sapra Luxmi²,Vishnoi Ankit¹,Srivastava Prateek³

Affiliation:

1. Systemics Cluster, School of Computer Science, University of Petroleum and Energy Studies,Dehradun,India

2. School of Computing, Graphic Era Hill University,Dehradun,India

3. Graphic Era Hill University,Department of Computer Science and Engineering,Dehradun,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10009018/10009023/10009527.pdf?arnumber=10009527

Reference19 articles.

1. Predictive Performances of Ensemble Machine Learning Algorithms in Landslide Susceptibility Mapping Using Random Forest, Extreme Gradient Boosting (XGBoost) and Natural Gradient Boosting (NGBoost)

2. Optimizing Predictions of Brain Stroke Using Machine Learning;telu;Journal of Neutrosophic and Fuzzy Systems (JNFS),2022

3. FURIA: an algorithm for unordered fuzzy rule induction

4. An Elderly Health Monitoring System Using Machine Learning and In-Depth Analysis Techniques on the NIH Stroke Scale

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