{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T20:15:46Z","timestamp":1649189746044},"reference-count":19,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Wavelets Multiresolut Inf. Process."],"published-print":{"date-parts":[[2016,3]]},"abstract":"<jats:p> In this paper, we propose a novel semi-supervised multi-category classification method based on one-dimensional (1D) multi-embedding. Based on the multiple 1D embedding based interpolation technique, we embed the high-dimensional data into several different 1D manifolds and perform binary classification firstly. Then we construct the multi-category classifiers by means of one-versus-rest and one-versus-one strategies separately. A weight strategy is employed in our algorithm for improving the classification performance. The proposed method shows promising results in the classification of handwritten digits and facial images. <\/jats:p>","DOI":"10.1142\/s0219691316400063","type":"journal-article","created":{"date-parts":[[2016,1,11]],"date-time":"2016-01-11T02:21:09Z","timestamp":1452478869000},"page":"1640006","source":"Crossref","is-referenced-by-count":3,"title":["1D embedding multi-category classification methods"],"prefix":"10.1142","volume":"14","author":[{"given":"Luoqing","family":"Li","sequence":"first","affiliation":[{"name":"Hubei Key Laboratory of Applied Mathematics, Faculty of Mathematics and Statistics, Hubei University, Wuhan 430062, P. R. China"}]},{"given":"Chuanwu","family":"Yang","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory of Applied Mathematics, Faculty of Mathematics and Statistics, Hubei University, Wuhan 430062, P. R. 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