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Publication: IIP Proceedings Year: 2022, Month: November Page No: 207-226, ISSN/ISBN: 978-81-959356-3-5, DOI/Link: https://rsquarel.org/assets/docupload/rsl20236207945B11C6D21.pdf
EARLY SYMPTOM IDENTIFICATION TECHNIQUES FOR CARDIOVASCULAR DISEASE DATA USING CLUSTER-BASED CLASSIFICATION TECHNIQUES
Area/Stream: Computing Technologies and Data Sciences, Authors: Raju Manjhi,Dr. Rahul Deo Sah, Syed Jaffar Abbas, Dr. Rajendra Kumar Mahto Keywords: Early Symptoms, Cardiovascular, Cluster Book Name /series: Futuristic Trends in Computing Technologies and Data Sciences,Volume 2, Book 18, Part 4, Chapter 1Publication: IIP Proceedings Year: 2022, Month: November Page No: 207-226, ISSN/ISBN: 978-81-959356-3-5, DOI/Link: https://rsquarel.org/assets/docupload/rsl20236207945B11C6D21.pdf
Abstract:
Data mining tools for medical sciences to analyse disease indicators are becoming more flexible and useful every day. Numerous cutting-edge data mining methods exist, such as mining data for various industries, mining application techniques like Nave Bays mining, clustering techniques, and other classification algorithms. The ensemble classifier process is advantageous for individual classification methods including artificial neural networks (ANNs), decision trees, and support vector machines. A novel ensemble classifier paradigm is a cluster-oriented ensemble technique for data classification. Keywords:- data mining technique, early cardiac signs, SVM, Ann.
Cite this: Raju Manjhi,Dr. Rahul Deo Sah, Syed Jaffar Abbas, Dr. Rajendra Kumar Mahto,"EARLY SYMPTOM IDENTIFICATION TECHNIQUES FOR CARDIOVASCULAR DISEASE DATA USING CLUSTER-BASED CLASSIFICATION TECHNIQUES", Futuristic Trends in Computing Technologies and Data Sciences,Volume 2, Book 18, Part 4, Chapter 1, November, 2022, 207-226, 978-81-959356-3-5, https://rsquarel.org/assets/docupload/rsl20236207945B11C6D21.pdf
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