Boosting Interval-Based Literals : Variable Length and Early Classification *

This work presents a system for supervised time series classification, capable of learning from series of different length and able of providing a classification when only part of the series are presented to the classifier. The induced classifiers consist of a linear combination of literals, obtained by boosting base classifiers that contain only one… (More)