dc.description.abstract |
Machine learning and data mining play a vital role in health care and also medical
information and detection, Now a day machine learning techniques use awareness of some
major health risks such as diabetic prediction, brain tumor detection, covid 19 detections,
and many more. The kidney is the most important organ of our body and if it has any
problem then the impact is more dangerous to our body. Chronic kidney disease (CKD),
otherwise referred to as renal disease. Chronic kidney disease requires disorders that
damage and reduce the capacity of our kidneys to keep us healthy. So, we need to be
concerned about kidney disease to our very primary stage. We take a few attributes to
measure our analysis about chronic kidney disease and this attribute is one of the major
occurrences of chronic kidney disease. Therefore 8 machine learning classifier are used to
measure analysis using weka tools namely: Naive Bayes(NB), Logistic Regression(LG),
Multilayer Perceptron(MLP), Stochastic Gradient Descent(SGD), Adaptive
Boosting(Adaboost), Bagging, Decision Tree(DT), Random Forest(RF) classifier are used.
We feature extraction of all attributes using principal component analysis(PCA). We gain
the highest accuracy from the Random Forest(RF) and it is 99% and ROC(receiver
operating characteristic) curve value is also highest from other algorithms |
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