{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T02:29:20Z","timestamp":1762050560529,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,5,11]],"date-time":"2022-05-11T00:00:00Z","timestamp":1652227200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Education, Science and Technological Development, Republic of Serbia","award":["TR32044"],"award-info":[{"award-number":["TR32044"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>The preprocessing of data is an important task in rough set theory as well as in Entropy. The discretization of data as part of the preprocessing of data is a very influential process. Is there a connection between the segmentation of the data histogram and data discretization? The authors propose a novel data segmentation technique based on a histogram with regard to the quality of a data discretization. The significance of a cut\u2019s position has been researched on several groups of histograms. A data set reduct was observed with respect to the histogram type. Connections between the data histograms and cuts, reduct and the classification rules have been researched. The result is that the reduct attributes have a more irregular histogram than attributes out of the reduct. The following discretization algorithms were used: the entropy algorithm and the Maximal Discernibility algorithm developed in rough set theory. This article presents the Cuts Selection Method based on histogram segmentation, reduct of data and MD algorithm of discretization. An application on the selected database shows that the benefits of a selection of cuts relies on histogram segmentation. The results of the classification were compared with the results of the Na\u00efve Bayes algorithm.<\/jats:p>","DOI":"10.3390\/e24050675","type":"journal-article","created":{"date-parts":[[2022,5,11]],"date-time":"2022-05-11T10:19:46Z","timestamp":1652264386000},"page":"675","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["The Cuts Selection Method Based on Histogram Segmentation and Impact on Discretization Algorithms"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4271-4549","authenticated-orcid":false,"given":"Visnja","family":"Ognjenovic","sequence":"first","affiliation":[{"name":"Technical Faculty \u201cMihajlo Pupin\u201d Zrenjanin, University of Novi Sad, 21102 Novi Sad, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7881-9217","authenticated-orcid":false,"given":"Vladimir","family":"Brtka","sequence":"additional","affiliation":[{"name":"Technical Faculty \u201cMihajlo Pupin\u201d Zrenjanin, University of Novi Sad, 21102 Novi Sad, Serbia"},{"name":"Faculty of Traffic Engineering, University of East Sarajevo, 74000 Doboj, Bosnia and Herzegovina"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2237-8026","authenticated-orcid":false,"given":"Jelena","family":"Stojanov","sequence":"additional","affiliation":[{"name":"Technical Faculty \u201cMihajlo Pupin\u201d Zrenjanin, University of Novi Sad, 21102 Novi Sad, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0958-9248","authenticated-orcid":false,"given":"Eleonora","family":"Brtka","sequence":"additional","affiliation":[{"name":"Technical Faculty \u201cMihajlo Pupin\u201d Zrenjanin, University of Novi Sad, 21102 Novi Sad, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2366-3942","authenticated-orcid":false,"given":"Ivana","family":"Berkovic","sequence":"additional","affiliation":[{"name":"Technical Faculty \u201cMihajlo Pupin\u201d Zrenjanin, University of Novi Sad, 21102 Novi Sad, Serbia"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,11]]},"reference":[{"key":"ref_1","first-page":"13","article-title":"The CRISP-DM model: The new blueprint for data mining","volume":"5","author":"Shearer","year":"2000","journal-title":"J. Data Warehous."},{"key":"ref_2","unstructured":"Ismail, M.K., and Ciesielski, V. (2003, January 14\u201317). An Empirical Investigation of the Impact of. Discretization on Common Data Distributions. In Proceedings of the Third International Conference on Hybrid Intelligent Systems (HIS\u201903): Design and Application of Hybrid Intelligent Systems, Melbourne, Australia."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Nguyen, H.S. (2006). Approximate boolean reasoning: Foundations and applications in data mining. Transactions on Rough Sets V, Springer.","DOI":"10.1007\/11847465_16"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Gama, J., and Pinto, C. (2006, January 23\u201327). Discretization from Data Streams: Applications to Histograms and Data Mining. Proceedings of the 2006 ACM Symposium on Applied computing, Dijon, France.","DOI":"10.1145\/1141277.1141429"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/S0262-8856(01)00095-6","article-title":"Multi-modal gray-level histogram modeling and decomposition","volume":"20","author":"Chang","year":"2002","journal-title":"Image Vis. Comput."},{"key":"ref_6","unstructured":"Ognjenovic, V. (2016). Approximative Discretization of Table-Organized Data. [Ph.D. Thesis, University of Novi Sad]. Available online: http:\/\/nardus.mpn.gov.rs\/bitstream\/handle\/123456789\/8685\/Disertacija13338.pdf?sequence=1&isAllowed=y."},{"key":"ref_7","first-page":"1","article-title":"Color image segmentation using histogram thresholding\u2014Fuzzy C-means hybrid approach","volume":"44","author":"Tan","year":"2001","journal-title":"Pattern Recognit."},{"key":"ref_8","unstructured":"Gonzalez, R.C., and Woods, R.E. (2002). Digital Image Processing, Prentice Hall."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/0734-189X(88)90022-9","article-title":"A survey of thresholding techniques","volume":"41","author":"Sahoo","year":"1988","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.1016\/j.patrec.2004.03.001","article-title":"Threshold selection based on cluster analysis","volume":"25","author":"Kwon","year":"2004","journal-title":"Pattern Recognit. Lett."},{"key":"ref_11","first-page":"141","article-title":"Automatic Delineation of Lung Parenchyma Based on Multilevel Thresholding and Gaussian Mixture Modelling","volume":"114","author":"Gopalakrishnan","year":"2018","journal-title":"Comput. Model. Eng. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1515","DOI":"10.1016\/j.patrec.2006.02.022","article-title":"Image segmentation by histogram thresholding using hierarchical cluster analysis","volume":"27","author":"Arifin","year":"2006","journal-title":"Pattern Recognit. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Mohapatra, S., Patra, D., and Kumar, K. (2011, January 3\u20135). Blood microscopic image segmentation using rough sets. Processing of the 2011 International Conference on Image Information Processing (ICIIP), Shimla, India.","DOI":"10.1109\/ICIIP.2011.6108977"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1885","DOI":"10.1007\/s11042-013-1723-2","article-title":"Medical image segmentation using rough set and local polynomial regression","volume":"74","author":"Xie","year":"2015","journal-title":"Multimed. Tools Appl."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.patcog.2017.05.012","article-title":"Learning features for offline handwritten signature verification using deep convolutional neural networks","volume":"70","author":"Hafemann","year":"2017","journal-title":"Pattern Recognit."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2083","DOI":"10.1016\/S0031-3203(00)00136-9","article-title":"Unimodal thresholding","volume":"34","author":"Rosin","year":"2001","journal-title":"Pattern Recognit."},{"key":"ref_17","unstructured":"UCI (2022, March 03). UC Irvine Machine Learning Repository. Available online: https:\/\/archive.ics.uci.edu\/ml\/index.html."},{"key":"ref_18","unstructured":"EasyFit Software (2016, March 17). Product Specification. Available online: http:\/\/www.mathwave.com\/products\/easyfit_desc.html."},{"key":"ref_19","unstructured":"Fayyad, U.M., and Irani, K.B. (September, January 28). The Attribute Selection Problem in Decision Tree Generation. Proceedings of the 13th International Joint Conference on Artificial Intelligence, Chambery, France."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Polkowski, L., and Skowron, A. (1998). The ROSETTA, software system. Rough Sets in Knowledge Discovery 2. Applications, Case Studies and Software Systems, Number 19 in Studies in Fuzziness and Soft Computing, Physica.","DOI":"10.1007\/978-3-7908-1883-3"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1002\/j.1538-7305.1948.tb01338.x","article-title":"A Mathematical Theory of Communication","volume":"27","author":"Shannon","year":"1948","journal-title":"Bell Syst. Tech. J."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Dobrilovic, D., Ognjenovic, V., Berkovic, I., and Radosav, D. (2021, January 13\u201315). Analyses of WSN\/UAV network configuration influences on 2.4 GHz IEEE 802.15.4 signal strength. Proceedings of the 2021 International Telecommunications Conference (ITC-Egypt), Alexandria, Egypt.","DOI":"10.1109\/ITC-Egypt52936.2021.9513956"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Lover, R. (2008). Elementary Logic: For Software Development, Springer Science & Business Media.","DOI":"10.1007\/978-1-84800-082-7"}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/24\/5\/675\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:09:09Z","timestamp":1760137749000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/24\/5\/675"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,11]]},"references-count":23,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2022,5]]}},"alternative-id":["e24050675"],"URL":"https:\/\/doi.org\/10.3390\/e24050675","relation":{},"ISSN":["1099-4300"],"issn-type":[{"type":"electronic","value":"1099-4300"}],"subject":[],"published":{"date-parts":[[2022,5,11]]}}}