{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T20:59:59Z","timestamp":1722977999558},"reference-count":34,"publisher":"International Academy Publishing (IAP)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JSW"],"DOI":"10.17706\/jsw.11.2.148-161","type":"journal-article","created":{"date-parts":[[2015,12,29]],"date-time":"2015-12-29T03:44:28Z","timestamp":1451360668000},"page":"148-161","source":"Crossref","is-referenced-by-count":0,"title":["Handling Sparse Data Sets by Applying Contrast Set Mining in Feature Selection"],"prefix":"10.17706","volume":"11","author":[{"name":"Faculty of Organization and Informatics, Pavlinska 2, 42000 Vara\u017edin, Croatia.","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dijana","family":"Ore\u0161ki","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mario","family":"Konecki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7163","published-online":{"date-parts":[[2016]]},"reference":[{"issue":"3","key":"ref1","first-page":"37","article-title":"From data mining to knowledge discovery in databases.","volume":"17","author":"Fayyad","year":"1996","unstructured":"[1] Fayyad, U., Piatetsky-Shapiro, G., & Smyth P. (1996). From data mining to knowledge discovery in databases. AI magazine, 17(3), 37-54.","journal-title":"AI Mag","ISSN":"http:\/\/id.crossref.org\/issn\/0738-4602","issn-type":"print"},{"key":"ref2","first-page":"1157","article-title":"An introduction to variable and feature selection.","volume":"3","author":"Guyon","year":"2003","unstructured":"[2] Guyon, I., & Elisseeff, A. (2003). An introduction to variable and feature selection. Journal of Machine Learning Research, 3, 1157-1182.","journal-title":"J Mach Learn Res","ISSN":"http:\/\/id.crossref.org\/issn\/1532-4435","issn-type":"print"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2010.12.160"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2012.05.023"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2013.05.051"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2008.08.007"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/956750.956781"},{"key":"ref8","first-page":"35","article-title":"Surface reconstruction from sparse data by a multiscale volumetric approach","volume-title":"Proceedings of the 5th WSEAS Int Conf on Signal Processing Computational Geometry & Artificial Vision","author":"Chimienhti","year":"2005","unstructured":"[9] Chimienhti, A., Dalmasso, P., Nerino, R., Pettiti, G., & Spertino, M. (2005). Surface reconstruction from sparse data by a multiscale volumetric approach, Proceedings of the 5th WSEAS Int. Conf. on Signal Processing, Computational Geometry & Artificial Vision (pp. 35-40). Malta, September 15-17."},{"key":"ref9","first-page":"395","article-title":"Feature selection with selective sampling.","volume-title":"Proceeding ICML 02 Proceedings of the Nineteenth International Conference on Machine Learning","author":"Liu","year":"2002","unstructured":"[10] Liu, H., Motoda, H., & Yu, L. (2002). Feature selection with selective sampling. Proceeding ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning (pp. 395-402)."},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/b978-1-55860-335-6.50023-4"},{"key":"ref11","first-page":"192","article-title":"Feature subset selection using the wrapper method: Overfitting and dynamic search space topology","volume-title":"Proceedings of the 1st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","author":"Kohavi","year":"1995","unstructured":"[12] Kohavi, R., & Sommerfield, D. (1995). Feature subset selection using the wrapper method: Overfitting and dynamic search space topology, Proceedings of the 1st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 192-197)."},{"key":"ref12","first-page":"284","article-title":"Toward optimal feature selection.","volume-title":"Proceedings of the Thirteenth International Conference on Machine Learning","author":"Koller","year":"1996","unstructured":"[13] Koller, D., & Sahami, M. (1996). Toward optimal feature selection. Proceedings of the Thirteenth International Conference on Machine Learning (pp. 284-292)."},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(97)00043-X"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/S1088-467X(97)00008-5"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/1277741.1277811"},{"issue":"1","key":"ref16","first-page":"14","article-title":"Unsupervised feature selection based on the distribution of features attributed to imbalanced data sets.","volume":"2","author":"Alibeigi","year":"2011","unstructured":"[17] Alibeigi, M. H. & S. Hamzeh, A. (2011). Unsupervised feature selection based on the distribution of features attributed to imbalanced data sets. International Journal of Artificial Intelligence and Expert Systems, 2(1), 14-22.","journal-title":"International Journal of Artificial Intelligence and Expert Systems"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijar.2010.02.001"},{"issue":"3","key":"ref18","doi-asserted-by":"crossref","first-page":"265","DOI":"10.3233\/IDA-2010-0421","article-title":"Empirical evaluation of feature selection methods in classification.","volume":"14","author":"Cehovin","year":"2010","unstructured":"[19] Cehovin, L., & Bosnic, Z. (2010). Empirical evaluation of feature selection methods in classification. Intelligent data analysis, 14(3), 265-281.","journal-title":"Intell Data Anal","ISSN":"http:\/\/id.crossref.org\/issn\/1088-467X","issn-type":"print"},{"issue":"5","key":"ref19","first-page":"756","article-title":"Analysis of feature selection with classification: Breast cancer datasets.","volume":"2","author":"Lavanya","year":"2011","unstructured":"[20] Lavanya, D., & Usha Rani, K. (2011). Analysis of feature selection with classification: Breast cancer datasets. Indian Journal of Computer Science and Engineering (IJCSE), 2(5), 756-763.","journal-title":"Indian Journal of Computer Science and Engineering"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.2298\/YJOR1101119N"},{"key":"ref21","volume-title":"The influence of feature selection methods on accuracy","author":"Haury","year":"2011","unstructured":"[22] Haury, A. C., Gestraud, P., & Vert, J. P. (2011). The influence of feature selection methods on accuracy. Stability and Interpretability of Molecular Signatures."},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2013.07.001"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1002\/widm.27"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1023\/A:1011429418057"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/170036.170072"},{"key":"ref26","first-page":"750","article-title":"Hierarchical categorization and the effects of contrast inconsistency in an unsupervised learning task.","volume-title":"Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society","author":"Davies","year":"1996","unstructured":"[29] Davies, J., & Bilman, D. (1996). Hierarchical categorization and the effects of contrast inconsistency in an unsupervised learning task. Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society (pp. 750-755)."},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1017\/cbo9780511921803"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2003.1245283"},{"key":"ref29","first-page":"1205","article-title":"Efficient feature selection via analysis of relevance and redundancy.","volume":"5","author":"Yu","year":"2004","unstructured":"[32] Yu, L. L., & Liu, L. (2004). Efficient feature selection via analysis of relevance and redundancy. Journal of Machine Learning Research, 5, 1205-1209.","journal-title":"J Mach Learn Res","ISSN":"http:\/\/id.crossref.org\/issn\/1532-4435","issn-type":"print"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/bfb0033278"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(97)00063-5"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-006-0030-1"},{"key":"ref33","first-page":"1","article-title":"Statistical comparisons of classifiers over multiple data Sets.","volume":"7","author":"Demsar","year":"2006","unstructured":"[36] Demsar, J. (2006). Statistical comparisons of classifiers over multiple data Sets. Journal of Machine Learning Research, 7, 1-30.","journal-title":"J Mach Learn Res","ISSN":"http:\/\/id.crossref.org\/issn\/1532-4435","issn-type":"print"},{"key":"ref34","volume-title":"Discovery analysis and presentation of strong rules","author":"Piatetsky-Shapiro","year":"1991","unstructured":"[37] Piatetsky-Shapiro, G. (1991). Discovery, analysis, and presentation of strong rules. Knowledge Discovery in Databases. 229-248, Menlo Park, CA: AAAI Press,"}],"container-title":["Journal of Software"],"original-title":[],"link":[{"URL":"http:\/\/www.jsoftware.us\/vol11\/132-JSW1542.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,3]],"date-time":"2019-09-03T00:46:57Z","timestamp":1567471617000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.jsoftware.us\/index.php?m=content&c=index&a=show&catid=164&id=2594"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"references-count":34,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2016]]}},"URL":"https:\/\/doi.org\/10.17706\/jsw.11.2.148-161","relation":{},"ISSN":["1796-217X"],"issn-type":[{"type":"electronic","value":"1796-217X"}],"subject":[],"published":{"date-parts":[[2016]]}}}