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

The advancement in sensing technology has enabled the development of various
applications for activity recognition using smartphone sensor data. One of the useful …

An increasing number of applications require to recognize the class of an incoming time
series as quickly as possible without unduly compromising the accuracy of the prediction. In …

More and more applications require early decisions, ie taken as soon as possible from
partially observed data. However, the later a decision is made, the more its accuracy tends …

A time series is an ordered sequence of measurements, called data points, recorded over
time. Generally, the term time series refers to univariate time series, where only one variable …

In this paper, an early time-series classification (ETSC) algorithm is applied to support fault
diagnosis in a complex hydraulic system (HS) with several interconnected components. The …

In numerous applications, for instance in predictive maintenance, there is a pression to
predict events ahead of time with as much accuracy as possible while not delaying the …

Learning to predict ahead of time events in open time series is challenging. While Early
Classification of Time Series (ECTS) tackles the problem of balancing online the accuracy of …

Early classification of time series is becoming increasingly a valuable task for assisting in
decision making process in many application domains. In this setting, information can be …

In numerous real-world situations, we have to make early decisions without complete
knowledge of the problem. The issue facing the decision makers is that, usually, the longer …