Читать книгу Computational Statistics in Data Science - Группа авторов - Страница 102

Developing efficient methods that can precisely predict future observations is one of the leading goals of data stream analysis. Yet, the intrinsic features of data stream, which include noisy characteristics, velocity, volume, variety, value, veracity, variability, and volatility, data stream analysis strongly constrain processing algorithms spatiotemporally. Hence, to guarantee high accuracy, mitigation of these challenges must be taken into consideration as they can negatively influence the accuracy of data stream analysis [39].