Machine Learning is used across many ranges around the world. The healthcare industry is no exclusion. Machine Learning can play an essential role in predicting presence/absence of locomotors disorders, Heart diseases and more. Such information, if predicted well in advance, can provide important intuitions to doctors who can then adapt their diagnosis and dealing per patient basis. We work on predicting possible Heart Diseases in people using Machine Learning algorithms. In this project we perform the comparative analysis of classifiers like decision tree, NaïveBayes, Logistic Regression, SVM and Random Forest and we propose an ensemble classifier which perform hybrid classification by taking strong and weak classifiers since it can have multiple number of samples for training and validating the data so weperform the analysis of existing classifier and proposed classifier like Ada-boost and XG-boost which can give the better accuracy and predictive analysis.
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I. Vasantha Kumari, working as an Assistant Professor in Computer Science and Engineering in Siddhartha Institute of Technology and Science Hyderabad1. She is having 10 years of academic experience. Her area of interest is Machine Learning and Artificial Intelligence .2. Dr. Anil Kumar Sahu is working as a Professor(ECE) in SITS, Hyderabad.
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Taschenbuch. Zustand: Neu. Machine Learning Approach n Heart Disease Predictions | A Complete Analysis | Vasantha Kumari Isukapalli (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206766681 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Artikel-Nr. 127634604
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