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Paperback

Heart Disease Prediction using Data Mining Techniques

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Heart disease is a common cause of death for people around the world. The overall examination on reasons for death because of coronary illness has been watched that it is the real reason for death. Analysis of these issues at beginning period helps the doctors in treating it at starting stage and to enhance the patient's wellbeing. In this manner the need to treat coronary illness that is found in individuals which precise entangled issues, if overlooked at beginning time. Different Data Mining Techniques can be used to analyze heart related issues. The essential point is an analysis of the Data Mining technique which is generally exact. There are different types of Data Mining Techniques such as Decision Tree, Naive Bayesian, Support Vector Machine (SVM), K-NN classifier, Hybrid Approach, Artificial Neural Network ANN). In this book, we analyze different classification algorithms.

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MORE INFO
Format
Paperback
Publisher
LAP Lambert Academic Publishing
Date
18 September 2024
Pages
60
ISBN
9786208116972

Heart disease is a common cause of death for people around the world. The overall examination on reasons for death because of coronary illness has been watched that it is the real reason for death. Analysis of these issues at beginning period helps the doctors in treating it at starting stage and to enhance the patient's wellbeing. In this manner the need to treat coronary illness that is found in individuals which precise entangled issues, if overlooked at beginning time. Different Data Mining Techniques can be used to analyze heart related issues. The essential point is an analysis of the Data Mining technique which is generally exact. There are different types of Data Mining Techniques such as Decision Tree, Naive Bayesian, Support Vector Machine (SVM), K-NN classifier, Hybrid Approach, Artificial Neural Network ANN). In this book, we analyze different classification algorithms.

Read More
Format
Paperback
Publisher
LAP Lambert Academic Publishing
Date
18 September 2024
Pages
60
ISBN
9786208116972