Abstract
This research aimed at classifying renal failure diseases whether acute renal failure (ARF) or chronic renal failure (CRF) based on linear discriminant analysis (LDA). The research was carried out by collecting data from patients with renal failure at Tobruk Medical Center (TMC). The sample was composed of 461 cases of renal failure, 238 cases of them were acute renal failure and 223 cases were chronic renal failure taking into account a set of crucial factors, including age, fasting blood sugar, urine, etc. The discriminant function analysis was applied using the R programming language. The study revealed that the linear discriminant analysis classified the two types and indicated that the variables with the highest impact on renal failure were creatinine and fat blood sugar. Also, the LDA was highly precise in classification, where 88.5% of the sample was classified successfully, which means a small error rate of 11.5%. Keywords: linear Discriminant Analysis, renal failure, classification.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
