Ensemble Learning for Enhanced Breast Cancer Detection: A Machine Learning Approach

Author(s)	Snigdha Bairi
Country	India
Abstract	Breast cancer is the most common cancer among women worldwide, with early detection being crucial for improved patient outcomes. Traditional machine learning algorithms have been employed in this domain, but their performance can be limited when dealing with complex medical datasets. This study investigates the potential of ensemble learning to enhance breast cancer detection accuracy. We implemented and evaluated popular ensemble learning methods on a well-established breast cancer dataset.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 5, Issue 5, September-October 2023
Published On	2023-10-19
Cite This	Ensemble Learning for Enhanced Breast Cancer Detection: A Machine Learning Approach - Snigdha Bairi - IJFMR Volume 5, Issue 5, September-October 2023. DOI 10.36948/ijfmr.2023.v05i05.7707
DOI	https://doi.org/10.36948/ijfmr.2023.v05i05.7707
Short DOI	https://doi.org/gswg5x

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9898-5948-55	editor@ijfmr.com

International Journal For Multidisciplinary Research