Predicting Chronic Kidney Disease Using Hybrid Machine Learning Based on Apache Spark

Table 1

Related works for prediction of CKD.

REF	Year	Models	Feature selection methods	Dataset
[22]	2021	SVM, KNN, DT, and RF	Recursive feature elimination (RFE)	CKD dataset
[20]	2020	ANN, C5.0, and LR	CFS, Lasso, and	CKD dataset
		LSVM, KNN, and RF	Wrapper method
[23]	2020	RF, SVM, NB, and LR	RF-FS, FS, FES, BS, and BES	CKD dataset
[24]	2020	An ensemble of decision tree models	Cost-sensitive ensemble	CKD dataset
			Feature ranking
[25]	2020	Bagging and random subspace	No	CKD dataset
		Methods based on KNN
		NB and DT
[26]	2020	Decision Table, J48	Genetic search algorithm	CKD dataset
		MLP and NB
[27]	2019	LR, RF, SVM, KNN	No	CKD dataset
		NB and FNN
		A hybrid model LR and RF
[28]	2019	Artificial neural network (ANN) and SVM	Correlation coefficients	CKD dataset
[29]	2018	NB and K-Star	No	CKD dataset
		SVM
		J48
[30]	2018	AdaBoost and KNN	CFS	CKD dataset
		NB and SVM