Performance Analysis of Distance Measures in K-Nearest Neighbor

Pulungan, A F and Zarlis, M and Suwilo, S (2020) Performance Analysis of Distance Measures in K-Nearest Neighbor. In: ICMASES 2019, 9-10 February 2019, Malang, Indonesia.

[thumbnail of PDF]
Preview
Text (PDF)
eai.3-8-2019.2290748.pdf - Published Version

Download (460kB) | Preview

Abstract

K-Nearest Neighbor (KNN) has important parameters that affect the performance of the KNN. The parameter is the k value and distance matrix. In KNN, the distance between two points is determined by the calculation of the distance matrix. In this paper, we will analyze and compare the performance KNN using the distance function. The distance is Braycurtis, Canberra and Euclidean Distance. This study uses Confusion Matrix for evaluation of accuracy, sensitivity, and specificity. The results showed that the Braycurtis distance had better performance than Canberra Distance and Euclidean Distance with accuracy values of 96%, sensitivity of 96.8% and specificity of 98.2%.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: classification k-nearest neighbor braycurtis distance canberra distance euclidean distance confusion matrix
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Depositing User: EAI Editor IV
Date Deposited: 25 Aug 2021 07:08
Last Modified: 25 Aug 2021 07:08
URI: https://eprints.eudl.eu/id/eprint/6302

Actions (login required)

View Item
View Item