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Synopsis
In the medical world, stroke is one of the most prominent diseases that threaten human life in the world. The most common causes of death in the world are stroke, heart disease and cancer. Fortunately, stroke can be prevented if high risks patients are identified before the occurrence of a stroke. A medical diagnosis for stroke prediction is a complex process. However, machine learning algorithms can be used to facilitate stroke prediction in the early stages. The performance of the classification algorithms depends on a balanced dataset hence this study aims to implement the imbalanced data techniques as undersampling, oversampling and hybrid techniques to enhance the classification models performance.
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Stroke Prediction Using Machine Learning Algorithms
Edité par
LAP LAMBERT Academic Publishing, 2022
ISBN 10 : 6139961939
ISBN 13 : 9786139961931
Neuf
Kartoniert / Broschiert
Vendeur : moluna, Greven, Allemagne
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Kartoniert / Broschiert. Etat : New. N° de réf. du vendeur 578587858
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Stroke Prediction Using Machine Learning Algorithms
Edité par
LAP LAMBERT Academic Publishing Mrz 2022, 2022
ISBN 10 : 6139961939
ISBN 13 : 9786139961931
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the medical world, stroke is one of the most prominent diseases that threaten human life in the world. The most common causes of death in the world are stroke, heart disease and cancer. Fortunately, stroke can be prevented if high risks patients are identified before the occurrence of a stroke. A medical diagnosis for stroke prediction is a complex process. However, machine learning algorithms can be used to facilitate stroke prediction in the early stages. The performance of the classification algorithms depends on a balanced dataset hence this study aims to implement the imbalanced data techniques as undersampling, oversampling and hybrid techniques to enhance the classification models performance. 80 pp. Englisch. N° de réf. du vendeur 9786139961931
Quantité disponible : 2 disponible(s)
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Stroke Prediction Using Machine Learning Algorithms : Artificial Intelligence (AI)
Edité par
LAP LAMBERT Academic Publishing, 2022
ISBN 10 : 6139961939
ISBN 13 : 9786139961931
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the medical world, stroke is one of the most prominent diseases that threaten human life in the world. The most common causes of death in the world are stroke, heart disease and cancer. Fortunately, stroke can be prevented if high risks patients are identified before the occurrence of a stroke. A medical diagnosis for stroke prediction is a complex process. However, machine learning algorithms can be used to facilitate stroke prediction in the early stages. The performance of the classification algorithms depends on a balanced dataset hence this study aims to implement the imbalanced data techniques as undersampling, oversampling and hybrid techniques to enhance the classification models performance. N° de réf. du vendeur 9786139961931
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Stroke Prediction Using Machine Learning Algorithms
Edité par
LAP LAMBERT Academic Publishing Mär 2022, 2022
ISBN 10 : 6139961939
ISBN 13 : 9786139961931
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Neuware -In the medical world, stroke is one of the most prominent diseases that threaten human life in the world. The most common causes of death in the world are stroke, heart disease and cancer. Fortunately, stroke can be prevented if high risks patients are identified before the occurrence of a stroke. A medical diagnosis for stroke prediction is a complex process. However, machine learning algorithms can be used to facilitate stroke prediction in the early stages. The performance of the classification algorithms depends on a balanced dataset hence this study aims to implement the imbalanced data techniques as undersampling, oversampling and hybrid techniques to enhance the classification models performance.Books on Demand GmbH, Überseering 33, 22297 Hamburg 80 pp. Englisch. N° de réf. du vendeur 9786139961931
Quantité disponible : 2 disponible(s)