Introduction to machine learning: k-nearest neighbors.

By Wentao Bao. Annals of Translational Medicine, 2016

1,098 citations recorded by the source corpus.

Machine learning techniques have been widely used in many scientific fields, but its use in medical literature is limited partly because of technical difficulties. k-nearest neighbors (kNN) is a simple method of machine learning. The article introduces some basic ideas underlying the kNN algorithm, and then focuses on how to perform kNN modeling with R. The dataset should be prepared before running the knn() function in R. After prediction of outcome with kNN algorithm, the diagnostic performance of the model should be checked. Average accuracy is the mostly widely used statistic to reflect the kNN algorithm. Factors such as k value, distance calculation and choice of appropriate predictors all have significant impact on the model performance.

Subfields: Artificial Intelligence, Signal Processing

View Paper: https://www.semanticscholar.org/paper/73811a7f8b89de1b8bdad6bb938e58059a9076d3

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In Artificial Intelligence

1. S. Omer
2. A. Malik

Citations in the corpus

• Distinguishing features of long COVID identified through immune profiling (2022, methodology): “A k of 10 was chosen by heuristic as approximately equal to the square root of the number of samples included 76 .”