Diabetes Prediction Using Feature Engineering Approach: Forecasting Diabetes Risk: Unleashing the Power of Feature Engineering and Hybrid Random Forest Algorithm - Softcover

Ramasamy, Gunavathi; Senthil Kumar, B.

 
9786207458707: Diabetes Prediction Using Feature Engineering Approach: Forecasting Diabetes Risk: Unleashing the Power of Feature Engineering and Hybrid Random Forest Algorithm
Softcover
ISBN 10: 6207458702 ISBN 13: 9786207458707
Verlag: LAP LAMBERT Academic Publishing, 2024

Inhaltsangabe

The fundamental notions behind diabetes mellitus and its types, causes, diagnosis, and significance in the prediction of DM. This technical work gives a short introduction to Data Mining and Machine Learning techniques for the prediction of diabetes mellitus. The different methodologies, techniques, and methods involved in predicting diabetes disease. Additionally, current advances in machine learning were highlighted, which have had a substantial influence on the identification and treatment of diabetes. The entire automatic disease prediction system utilizes data collection, noise removal, feature extraction, selection, and classification techniques. The described steps are examined in different authors perceptively to get the better knowledge about particular steps. The class imbalance problem on medical data and applied sampling technique is evaluated with different iteration which denotes the number of sampling process. Adaptive sampling technique is adopted for balancing the class in medical dataset. This improves the performance of the gradient boosting classifier that provides 97.78% accuracy.

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Über die Autorin bzw. den Autor

R. Gunavathi est actuellement professeur associé à Christ (université réputée). Elle a formé 17 chercheurs et publié plus de 80 articles dans Scopus et dans des revues réputées. Mme R.Shiddharthy, actuellement professeur adjoint au Nallamuthu Gounder Mahalingam College, a publié 4 articles dans des revues réputées.

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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2024
Sprache
Englisch
ISBN 10 
6207458702
ISBN 13 
9786207458707
Einband
Taschenbuch
Anzahl der Seiten
192
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
Edicoes Nosso Conhecimento
customerservice@vdm-vsg.de

SIA
Riga
1039
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