Neuware -Data mining is a vital role in several applications such as business organizations, educational institutions, government sectors, health care industry, scientific and engineering.In the health care industry, the data mining is predominantly used for disease prediction.The main objective is to predict kidney diseases using classification algorithms such as Naive Bayes and Support Vector Machine. This mainly focused on finding the best classification algorithm based on the classification accuracy and execution time performance factors.This algorithm takes symptoms as input and predicts the disease based on patients data.Books on Demand GmbH, �berseering 33, 22297 Hamburg 60 pp. Englisch.

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T�tulo: Data Mining Classification Algorithms For Kidney Disease Prediction
Editor: LAP LAMBERT Academic Publishing Mai 2021
Fecha de publicaci�n: 2021
Idioma: Ingl�s
ISBN 10: 6203863092
ISBN 13: 9786203863093
Encuadernaci�n: Taschenbuch
Estado: Neu

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Data mining is a vital role in several applications such as business organizations, educational institutions, government sectors, health care industry, scientific and engineering.In the health care industry, the data mining is predominantly used for disease prediction.The main objective is to predict kidney diseases using classification algorithms such as Naive Bayes and Support Vector Machine. This mainly focused on finding the best classification algorithm based on the classification accuracy and execution time performance factors.This algorithm takes symptoms as input and predicts the disease based on patients data.<p>Data mining is a vital role in several applications such as business organizations, educational institutions, government sectors, health care industry, scientific and engineering.In the health care industry, the data mining is predominantly used for disease prediction.The main objective is to predict kidney diseases using classification algorithms such as Naive Bayes and Support Vector Machine. This mainly focused on finding the best classification algorithm based on the classification accuracy and execution time performance factors.This algorithm takes symptoms as input and predicts the disease based on patients data.</p>

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