Cross-Validation and Validation Set Methods for Choosing K in KNN Algorithm for Healthcare Case Study

Rahim, Robbi and Ansari Saleh, Ahmar and Rahmat, Hidayat (2022) Cross-Validation and Validation Set Methods for Choosing K in KNN Algorithm for Healthcare Case Study. JINAV: Journal of Information and Visualization, 3 (1). pp. 57-61.

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Abstract

KNN categorization is simple and successful in healthcare. In this research’s example case study, the KNN algorithm classified the new record as “Abnormal.” The classification method began with choosing K, then calculating the Euclidean distance between the new record and the training set, finding the K nearest neighbors, then classifying the new record based on those K neighbors. The findings show that the KNN algorithm is effective in healthcare and highlight several shortcomings that should be addressed in future study. Weighting variables, choosing the best K value, and handling non-uniform data are these restrictions. The findings show the KNN algorithm’s medical potential.

Item Type:	Article
Subjects:	KARYA ILMIAH DOSEN Universitas Negeri Makassar > KARYA ILMIAH DOSEN
Divisions:	KOLEKSI KARYA ILMIAH UPT PERPUSTAKAAN UNM MENURUT FAKULTAS > KARYA ILMIAH DOSEN KARYA ILMIAH DOSEN
Depositing User:	Ansari Saleh Ahmar
Date Deposited:	08 May 2023 10:08
Last Modified:	08 May 2023 10:08
URI:	http://eprints.unm.ac.id/id/eprint/28634

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