… Kidney Disease. To diagnose the Chronic Kidney Disease, two essential types of feature
selection … to reduce the dimension of Chronic Kidney Disease dataset. In wrapper approach, …

… Chronic kidney disease is a fatal illness of kidney which can be … Kidney Disease dataset
collected from UCI repository, was investigated to predict the presence of kidney disease. Data …

… This paper proposed an approach that combines information-gain-based feature selection
and a cost-sensitive AdaBoost classifier to improve the detection of chronic kidney disease. …

… of morbidity and mortality, chronic kidney disease (CKD) is a significant … kidney disease
using different Machine Learning (ML) algorithms with the support of a hybrid feature selection …

… excluding those with pre-existing kidney disease, and utilized all available … feature selection
methods in conjunction with 6 feature ensemble techniques for selecting top-ranked features …

… for chronic kidney disease, but … feature selection in enhancing CKD classification. This
study aims to enhance the quality of chronic kidney disease classification with feature selection …

… The main task of this research work is to identify and classify the chronic kidney disease (CKD)
using the data mining based classification and propose a new feature selection …

… The dataset used in this paper is the chronic kidney disease (… of disease and ‘0’ representing
absence of disease. There … patients suffering from chronic kidney disease. The experiments …

… To predict chronic kidney disease, build two important models. Namely, feature selection
method and ensemble model. To build chronic kidney disease prediction, used Info gain …

… chronic kidney disease is analyzed because of a showing of people distinguished to be in
danger of kidney … Feature selection and dimension reduction are fundamental walks in pattern …