Time series data is increasingly used in a wide range of fields, and it is often relied on in
crucial applications and high-stakes decision-making. For instance, sensors generate time …

Predictive business process monitoring refers to the act of making predictions about the
future state of ongoing cases of a business process, based on their incomplete execution …

Early classification of time series has been extensively studied for minimizing class
prediction delay in time-sensitive applications such as medical diagnostic and industrial …

Multivariate time series (MTS) data are widely used in a very broad range of fields, including
medicine, finance, multimedia and engineering. In this paper a new approach for MTS …

The multivariate time series (MTS) classification is a very difficult process because of the
complexity of the MTS data type. Among all the methods to resolve this problem, the attribute …

Electronic health records contain large amounts of longitudinal data that are valuable for
biomedical informatics research. The application of machine learning is a promising …

Multivariate time series (MTS) classification is an important topic in time series data mining,
and has attracted great interest in recent years. However, early classification on MTS data …

Early time series classification predicts the class label of a given time series before it is
completely observed. In time-critical applications, such as arrhythmia monitoring in ICU …

In recent years, early classification on time series has become increasingly important in time-
sensitive applications. Existing shapelet based methods still cannot work well on this …

Time series shapelets are discriminative subsequences and their similarity to a time series
can be used for time series classification. Since the discovery of time series shapelets is …