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Further, different aspects of our proposed \"Artificial endocrine system for knowledge discovery\" (AESKD) have been compared with state of art classifiers e.g., support vector machine, neural network, radial basis function (RBF) network and K-NN for some bench mark datasets. <\/jats:p>","DOI":"10.1142\/s0219878913500150","type":"journal-article","created":{"date-parts":[[2014,1,13]],"date-time":"2014-01-13T03:57:42Z","timestamp":1389585462000},"page":"1350015","source":"Crossref","is-referenced-by-count":1,"title":["ARTIFICIAL ENDOCRINE SYSTEM: A NEW PARADIGM OF KNOWLEDGE DISCOVERY"],"prefix":"10.1142","volume":"09","author":[{"given":"SUBHASH CHANDRA","family":"PANDEY","sequence":"first","affiliation":[{"name":"Computer Science and Engineering Department, Birla Institute of Technology, Mesra, Ranchi (Allahabad Campus), Allahabad, UP, India"}]},{"given":"GORA CHAND","family":"NANDI","sequence":"additional","affiliation":[{"name":"Artificial Intelligence and Robotics Lab, Indian Institute of Information Technology, Allahabad, UP, India"}]}],"member":"219","published-online":{"date-parts":[[2014,5,19]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.96.12.6745"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1201\/9781420034349"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-04378-3"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1210\/jcem-35-1-126"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1210\/jcem-35-1-144"},{"key":"rf7","first-page":"9","volume":"19","author":"Danziger L.","journal-title":"Bullet. 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