A Study Machine Learning Techniques for Event Prediction through Neurophysiological data: an Epilepsy case study
event prediction, epilepsy, ensembles
Event prediction from neurophysiological data has many variables which must be analyzed in different moments, since data acquisition and registry to its post-processing. Hence, choosing the algorithm that will process these data is a very important step, for processing time and accuracy of results are determinant factors for a diagnosis auxiliary tool. Tasks of classification and prediction also help in understanding brain cell's networks interactions. This work studies Data Mining techniques with different features to analyzing their impact on the task of event prediction from neurophysiological data and purposes use of ensembles to optimize the performance of event prediction task through computational low-cost techniques.