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

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.