Time-series classification is the common theoretical background of many recognition tasks
performed by computers such as handwriting recognition speech recognition or detection of
abnormalities in electrocardiograph signals. In this book the state-of-the-art in time-series
classification is surveyed and five new techniques are presented. Four out of them aim at
making the recognition more accurate while the proposed instance-selection algorithm speeds up
time-series classification. Besides time-series classification tasks potential applications of
the proposed techniques include problems from various domains e.g. web science or medicine.
