<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:DOC-KTZH2SJD</identifier><date>2025</date><creator>Sun, Y. Y.</creator><relation>documents/doc/K/URN_NBN_SI_doc-KTZH2SJD_001.pdf</relation><relation>documents/doc/K/URN_NBN_SI_doc-KTZH2SJD_001.txt</relation><format format_type="issue">2</format><format format_type="volume">20</format><format format_type="type">article</format><format format_type="extent">str. 157-172</format><identifier identifier_type="DOI">10.14743/apem2025.2.533</identifier><identifier identifier_type="ISSN">1854-6250</identifier><identifier identifier_type="COBISSID_HOST">265536003</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-KTZH2SJD</identifier><language>eng</language><publisher publisher_location="Maribor">Fakulteta za strojništvo, Inštitut za proizvodno strojništvo</publisher><source>Advances in production engineering and management</source><rights>BY</rights><subject language_type_id="slv">analiza procesov</subject><subject language_type_id="eng">C5.0 decision tree algorithms</subject><subject language_type_id="eng">defect prediction</subject><subject language_type_id="eng">industrial data mining</subject><subject language_type_id="slv">inteligentna proizvodnja</subject><subject language_type_id="eng">intelligent manufacturing</subject><subject language_type_id="eng">machine learning</subject><subject language_type_id="slv">napovedovanje napak</subject><subject language_type_id="slv">procesna industrija</subject><subject language_type_id="eng">process industry</subject><subject language_type_id="eng">process-oriented analytics</subject><subject language_type_id="eng">random forest</subject><subject language_type_id="slv">strojno učenje</subject><title>Enhanced product defect forecasting using partitioned attributes and ensemble machine learning</title></Record>