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Heart Disease Data Classification using Data Mining Techniques - Bl Deekshatulu,Akhil Jabbar Meerja

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2019-03-25
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This book is an essential reference work for academicians, professionals, researchers, and students interested in the relationship between data mining and medical database. This book offers an overview of machine learning technologies and evolutionary techniques in decision support systems for the diagnosis of heart disease based on medical data. Data collected from various hospitals were selected and prepr ... Visas aprašymas

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This book is an essential reference work for academicians, professionals, researchers, and students interested in the relationship between data mining and medical database. This book offers an overview of machine learning technologies and evolutionary techniques in decision support systems for the diagnosis of heart disease based on medical data. Data collected from various hospitals were selected and preprocessed for this study. These techniques are used to explore risk factors associated with heart disease. This book also covers state-of-the-art research toward developing a decision support system for heart disease prediction with machine learning approaches. The book presents numerous techniques, algorithms, and models. It describes neural networks, evolutionary techniques like genetic algorithms, associative classification, and statistical models, and machine learning approaches for heart disease prediction. We discussed how these machine learning techniques are used to classify heart disease data sets.

Daugiau informacijos

Autorius Bl Deekshatulu, Akhil Jabbar Meerja
Leidėjas LAP LAMBERT Academic Publishing
Išleidimo metai 2019
Viršelio tipas Minkšti viršeliai
EAN 9786139464289
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83,01 € 110,68 €