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A wide range of algorithms was tested, and those with the best performance were chosen for further tuning and analysis. Our resulting recognizer, RATA.Gesture, is an ensemble of four algorithms. We evaluated it against four popular gesture recognizers with three data sets; one of our own and two from other projects. Except for recognizer\u2013data set pairs (e.g., PaleoSketch recognizer and PaleoSketch data set) the results show that it outperforms the other recognizers. This demonstrates the potential of this approach to produce flexible and accurate recognizers.<\/jats:p>","DOI":"10.1017\/s0890060412000194","type":"journal-article","created":{"date-parts":[[2012,8,14]],"date-time":"2012-08-14T13:10:25Z","timestamp":1344949825000},"page":"351-366","source":"Crossref","is-referenced-by-count":6,"title":["RATA.Gesture: A gesture recognizer developed using data mining"],"prefix":"10.1017","volume":"26","author":[{"given":"Samuel Hsiao-Heng","family":"Chang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rachel","family":"Blagojevic","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Beryl","family":"Plimmer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2012,8,14]]},"reference":[{"key":"S0890060412000194_ref51","unstructured":"Yu B. , & Cai S. (2003). 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