Fusion methods for time-series classification /
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| Author / Creator: | Buza, Krisztian Antal. |
|---|---|
| Imprint: | Frankfurt am Main ; New York : Peter Lang, c2011. |
| Description: | xiii, 144 p. : ill. ; 22 cm. |
| Language: | English |
| Series: | Informationstechnologie und Ökonomie, 1616-086x ; Bd. 45 Informationstechnologie und Ökonomie ; Bd. 45. |
| Subject: | |
| Format: | Dissertations Print Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/8682100 |
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| 008 | 111208s2011 gw a bm 000 0 eng d | ||
| 020 | |a 9783631630853 | ||
| 020 | |a 3631630859 | ||
| 035 | |a (OCoLC)768169079 | ||
| 040 | |a BTCTA |b eng |c BTCTA |d YDXCP |d BWK |d CUV |d RRP | ||
| 049 | |a CGUA | ||
| 090 | |a QA280 |b .B89 2011 | ||
| 100 | 1 | |a Buza, Krisztian Antal. | |
| 245 | 1 | 0 | |a Fusion methods for time-series classification / |c Krisztian Antal Buza. |
| 260 | |a Frankfurt am Main ; |a New York : |b Peter Lang, |c c2011. | ||
| 300 | |a xiii, 144 p. : |b ill. ; |c 22 cm. | ||
| 336 | |a text |b txt |2 rdacontent |0 http://id.loc.gov/vocabulary/contentTypes/txt | ||
| 337 | |a unmediated |b n |2 rdamedia |0 http://id.loc.gov/vocabulary/mediaTypes/n | ||
| 338 | |a volume |b nc |2 rdacarrier |0 http://id.loc.gov/vocabulary/carriers/nc | ||
| 490 | 1 | |a Informationstechnologie und Ökonomie, |x 1616-086x ; |v Bd. 45 | |
| 502 | |a Originally presented as the author's dissertation--Universität Hildesheim, 2011. | ||
| 504 | |a Includes bibliographical references (p. [127]-144). | ||
| 505 | 0 | |a Individual quality estimation -- Instance selection -- Fusion of distance measures -- The GRAMOFON ensemble framework -- Motifs for time-series classification -- Outlook: some related applications. | |
| 520 | 0 | |a "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"--Back cover. | |
| 650 | 0 | |a Time-series analysis. |0 http://id.loc.gov/authorities/subjects/sh85135430 | |
| 650 | 7 | |a Time-series analysis. |2 fast |0 http://id.worldcat.org/fast/fst01151190 | |
| 830 | 0 | |a Informationstechnologie und Ökonomie ; |v Bd. 45. | |
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| 927 | |t Library of Congress classification |a QA280 .B89 2011 |l JCL |c JCL-Sci |e WAGN |e CRERAR |b 104524617 |i 9019308 | ||
