Адаптивна матрична нейро-фаззі самоорганізовна мережа для кластеризації багатовимірних потоків даних
Time series clustering is wide spread problem in Data Stream Mining tasks and nowadays there are a lot of various approaches for solving such tasks that are based on different a priori assumptions. However, there are cases when well-known methods and algorithms for solving this task are inoperative in real applications. One of such tasks is short time series fuzzy clustering with unevenly distributed in time observations. The time series clustering of data set with missed observations is sufficiently close to this problem.