Fusion Methods for Time-Series Classification
Regular price
€36.50
14 days return policy
Shipping & Delivery
A01=Krisztian Buza
Author_Krisztian Buza
Buza
Category=GPF
Category=GPH
Category=JNF
Category=JPP
Category=KJ
Category=UB
Category=UBH
Category=UBJ
Category=UFL
Category=UY
eq_bestseller
eq_business-finance-law
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Product details
- ISBN 9783631630853
- Weight: 310g
- Dimensions: 148 x 210mm
- Publication Date: 25 Nov 2011
- Publisher: Peter Lang AG
- Publication City/Country: CH
- Product Form: Hardback
Secure
checkout
Fast Shipping
Easy returns
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.
Krisztian Antal Buza obtained his diploma at the Budapest University of Technology and Economics in 2007, and his PhD at the University of Hildesheim in 2011. His work on time-series classification was honored by the Best Paper Award at the renowned conference on Computational Science and Engineering of the Institute of Electrical and Electronics Engineers (IEEE) in 2010.
