Group Reverse kNN Query optimisation

Haryanto, Anasthasia Agnes; Taniar, David; Adhinugraha, Kiki Maulana

doi:10.1016/j.jocs.2015.09.006

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2015

2022

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Cited by 3 publications

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“…Repeat until the algorithm finds a new patient. This lets the computer forecast based on data patterns and relationships rather than human intuition, which would be impossible given the magnitude of data (Bilal et al, 2016;Ding et al, 2015;Haryanto et al, 2015).…”

Section: Introduction *mentioning

confidence: 99%

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

Rahim¹,

Ahmar

2022

jinav j. inf. vis.

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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.

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Section: Introduction *mentioning

confidence: 99%