{"id":"https://openalex.org/W2115369438","doi":"https://doi.org/10.1109/iti.2008.4588534","title":"A novel generic algorithm for cluster split iB-fold cross-validation","display_name":"A novel generic algorithm for cluster split iB-fold cross-validation","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2115369438","doi":"https://doi.org/10.1109/iti.2008.4588534","mag":"2115369438"},"language":"en","primary_location":{"id":"doi:10.1109/iti.2008.4588534","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iti.2008.4588534","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ITI 2008 - 30th International Conference on Information Technology Interfaces","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009651277","display_name":"Boris Ba\u010di\u0107","orcid":"https://orcid.org/0000-0003-0305-4322"},"institutions":[{"id":"https://openalex.org/I39854758","display_name":"Auckland University of Technology","ror":"https://ror.org/01zvqw119","country_code":"NZ","type":"education","lineage":["https://openalex.org/I39854758"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Boris Bacic","raw_affiliation_strings":["School of Computing and Mathematical Sciences, Faculty of Design and Creative Technologies, Auckland University of Technology, New Zealand","Sch. of Comput. & Math. Sci., Auckland Univ. of Technol., Auckland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Mathematical Sciences, Faculty of Design and Creative Technologies, Auckland University of Technology, New Zealand","institution_ids":["https://openalex.org/I39854758"]},{"raw_affiliation_string":"Sch. of Comput. & Math. Sci., Auckland Univ. of Technol., Auckland","institution_ids":["https://openalex.org/I39854758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5009651277"],"corresponding_institution_ids":["https://openalex.org/I39854758"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1556504,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"919","last_page":"924"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.780383825302124},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.6044600009918213},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5022644996643066},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4993164539337158},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.48227646946907043},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4737734794616699},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.45324626564979553},{"id":"https://openalex.org/keywords/fold","display_name":"Fold (higher-order function)","score":0.4304662346839905},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4232792258262634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41278234124183655},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40640315413475037},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10431241989135742},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08064255118370056}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.780383825302124},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.6044600009918213},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5022644996643066},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4993164539337158},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.48227646946907043},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4737734794616699},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45324626564979553},{"id":"https://openalex.org/C53942344","wikidata":"https://www.wikidata.org/wiki/Q951651","display_name":"Fold (higher-order function)","level":2,"score":0.4304662346839905},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4232792258262634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41278234124183655},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40640315413475037},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10431241989135742},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08064255118370056},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iti.2008.4588534","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iti.2008.4588534","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ITI 2008 - 30th International Conference on Information Technology Interfaces","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.854.3393","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.854.3393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://hnk.ffzg.hr/bibl/iti2008/PDF/%28113%29/113-01-090.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1538644830","https://openalex.org/W1597190145","https://openalex.org/W1808591511","https://openalex.org/W2137784590","https://openalex.org/W2179183114","https://openalex.org/W2889200856","https://openalex.org/W4312750805","https://openalex.org/W6685765206"],"related_works":["https://openalex.org/W1181095405","https://openalex.org/W3014426369","https://openalex.org/W4240318783","https://openalex.org/W4406253713","https://openalex.org/W2311285072","https://openalex.org/W1573293794","https://openalex.org/W783636722","https://openalex.org/W2292230535","https://openalex.org/W4243341329","https://openalex.org/W2293349767"],"abstract_inverted_index":{"This":[0],"article":[1],"proposes":[2],"a":[3,9,17,21,29],"point":[4],"of":[5,90,97],"view":[6],"(sub-space":[7],"modelling),":[8],"post-processing":[10],"strategy":[11,19],"(relating":[12],"to":[13,50,79],"sub-optimal":[14],"model)":[15],"and":[16,86,94],"pre-processing":[18],"involving":[20],"novel":[22],"cross-validation":[23],"algorithm":[24],"in":[25,47,67],"machine":[26],"learning":[27],"with":[28],"focus":[30],"on":[31,70],"small":[32,40],"datasets.":[33],"To":[34],"overcome":[35],"the":[36,91,95],"limitations":[37],"imposed":[38],"by":[39,87],"datasets,":[41],"this":[42],"approach":[43],"leverages":[44],"human":[45,71],"expertise":[46],"being":[48],"able":[49],"visualise":[51],"or":[52,61],"conceptualize":[53],"clusters":[54],"at":[55],"high":[56],"level":[57],"using":[58,84],"e.g.":[59],"proximity":[60],"similarity,":[62],"without":[63],"detailed":[64],"analysis.":[65],"Validation":[66],"case":[68],"studies":[69],"motion":[72],"have":[73],"shown":[74],"that":[75],"it":[76],"is":[77],"possible":[78],"achieve":[80],"better":[81],"modelling":[82],"results":[83],"iB-fold":[85],"leveraging":[88],"understanding":[89],"data":[92],"set":[93],"nature":[96],"validation.":[98]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}