Comparison between K-Nearest Neighbor and Support Vector Machine Algorithms for PPG Biometric Identification

Autor:	Aya Al Sidani, Ali Cherry, Mohamad Hajj-Hassan, Houssein Hajj-Hassan
Rok vydání:	2019
Předmět:	Support vector machine ComputingMethodologies_PATTERNRECOGNITION Biometrics Computer science business.industry Data classification Feature extraction Pattern recognition Artificial intelligence business k-nearest neighbors algorithm
Zdroj:	2019 Fifth International Conference on Advances in Biomedical Engineering (ICABME).
DOI:	10.1109/icabme47164.2019.8940333
Popis:	with the great evolution in information technology, data mining and its techniques became a need in almost every application. One of the data mining techniques is data classification, in this paper 2 classification techniques are compared, the K-nearest neighbor and the Support vector machine due to their several advantages. The classification techniques are implemented and tested on Photoplethysmography signals after extracting 40 features from the signals. This work was made in order to check the efficiency of using the Photoplethysmography signals as biometric identification technique and choose the best classification technique for this application.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8cbe0ce0b2f3de1a6bdbcae0bf71d86e https://doi.org/10.1109/icabme47164.2019.8940333 Zobrazit plný text záznamu