Fig. 4.

Flow diagrams of supervised classification machine learning algorithms. a Simplified diagram of discriminant analysis algorithm used to predict anesthesia drugs present in the human body. The algorithm used means and covariance in dimension reduction to increase the distance between the means and scatter. The last step checked the posterior probability, prior probability, and classification error before prediction. b The KNN algorithm analyzes PPG waveform features and measures Minkowski distances between the query point and three neighboring data points. Later, a majority check was performed to finalize the detection result of anesthesia/non-anesthesia patients. c A flow diagram of the SVM algorithm that shows the hyperplane and epsilon tolerance (surrounded by dashed lines) created by the support vectors