{"id":"https://openalex.org/W2998005563","doi":"https://doi.org/10.1145/3362752.3362763","title":"Support Vector Machine Pre-pruning Approaches on Decision Trees for Better Classification","display_name":"Support Vector Machine Pre-pruning Approaches on Decision Trees for Better Classification","publication_year":2019,"publication_date":"2019-09-25","ids":{"openalex":"https://openalex.org/W2998005563","doi":"https://doi.org/10.1145/3362752.3362763","mag":"2998005563"},"language":"en","primary_location":{"id":"doi:10.1145/3362752.3362763","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3362752.3362763","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 2nd International Conference on Electronics and Electrical Engineering Technology","raw_type":"proceedings-article"},"type":"article","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/A5027750980","display_name":"Doreen Ying Ying Sim","orcid":null},"institutions":[{"id":"https://openalex.org/I41461413","display_name":"Universiti Malaysia Sarawak","ror":"https://ror.org/05b307002","country_code":"MY","type":"education","lineage":["https://openalex.org/I41461413"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Doreen Ying Ying Sim","raw_affiliation_strings":["Universiti Malaysia Sarawak, Jalan Datuk Mohammad Musa, Kuching, Malaysia"],"affiliations":[{"raw_affiliation_string":"Universiti Malaysia Sarawak, Jalan Datuk Mohammad Musa, Kuching, Malaysia","institution_ids":["https://openalex.org/I41461413"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5027750980"],"corresponding_institution_ids":["https://openalex.org/I41461413"],"apc_list":null,"apc_paid":null,"fwci":0.14,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59470512,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"30","last_page":"36"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9977999925613403,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9977999925613403,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.992900013923645,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9927999973297119,"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/support-vector-machine","display_name":"Support vector machine","score":0.8564255237579346},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.7756293416023254},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.7296181917190552},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6849316358566284},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.6077470779418945},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.582410991191864},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.5378156900405884},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5331496596336365},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4839968681335449},{"id":"https://openalex.org/keywords/fraction","display_name":"Fraction (chemistry)","score":0.4488449990749359},{"id":"https://openalex.org/keywords/structural-risk-minimization","display_name":"Structural risk minimization","score":0.44261863827705383},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40969860553741455},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.363277792930603},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32413533329963684},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.22980770468711853}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8564255237579346},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7756293416023254},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.7296181917190552},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6849316358566284},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6077470779418945},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.582410991191864},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.5378156900405884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5331496596336365},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4839968681335449},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.4488449990749359},{"id":"https://openalex.org/C154507838","wikidata":"https://www.wikidata.org/wiki/Q7625053","display_name":"Structural risk minimization","level":3,"score":0.44261863827705383},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40969860553741455},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.363277792930603},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32413533329963684},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.22980770468711853},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3362752.3362763","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3362752.3362763","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 2nd International Conference on Electronics and Electrical Engineering Technology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7400000095367432,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1503183057","https://openalex.org/W1588648558","https://openalex.org/W2144960808","https://openalex.org/W2148603752","https://openalex.org/W2557866760","https://openalex.org/W2699648269","https://openalex.org/W2778721650","https://openalex.org/W2790367972","https://openalex.org/W2795216744","https://openalex.org/W2896774879","https://openalex.org/W2949149021","https://openalex.org/W2953235543","https://openalex.org/W6630096170"],"related_works":["https://openalex.org/W2373300491","https://openalex.org/W2395294869","https://openalex.org/W1566212037","https://openalex.org/W2099261031","https://openalex.org/W1949865450","https://openalex.org/W2052343155","https://openalex.org/W2155195660","https://openalex.org/W2103875979","https://openalex.org/W2057467996","https://openalex.org/W2052945097"],"abstract_inverted_index":{"Incorporation":[0],"of":[1,6,40,55,78,84,89,102,167,183],"the":[2,12,47,50,61,67,70,74,81,97,110,114,138,150,156,174,179,191],"structural":[3],"risk":[4,18],"minimization":[5,19],"Support":[7,31],"Vector":[8,32],"Machine":[9,33],"to":[10,22,46,113,120,158],"pre-prune":[11],"decision":[13,41],"trees":[14,42],"based":[15,95],"on":[16,69,96,178],"empirical":[17],"is":[20,28,44,58,91,118,162],"conducted":[21],"develop":[23],"a":[24,186],"combined":[25],"algorithm.":[26,38],"It":[27],"named":[29],"as":[30,147,149],"Pruned":[34],"Decision":[35],"Trees":[36],"(SVMPDT)":[37],"Pre-pruning":[39],"(DT)":[43],"applied":[45,106],"datasets":[48],"through":[49],"synergistically":[51],"adjusted":[52,94,135,172],"regularization":[53,82,87,165],"parameter":[54,83,88,134,166],"SVM.":[56,85],"This":[57,161],"done":[59],"by":[60],"proposed":[62,111,176],"new":[63],"approach":[64],"derived":[65],"from":[66,104],"study":[68],"synergy":[71,187],"effects":[72],"between":[73],"pre-pruning":[75],"weighting":[76,145,181],"fraction":[77,146,182],"DT":[79,103,140,157,184],"and":[80,93,100,137],"The":[86],"SVM":[90,130,168],"customized":[92],"different":[98],"features":[99],"characteristics":[101],"each":[105],"dataset.":[107],"After":[108],"applying":[109,143],"algorithms":[112,153],"assigned":[115],"datasets,":[116],"it":[117],"shown":[119],"be":[121,159,170,196],"more":[122],"accurate":[123],"in":[124,185],"classification":[125,141,192],"when":[126],"compared":[127],"with":[128,173],"typical":[129,139],"without":[131,142,154],"getting":[132,155],"its":[133,164],"accordingly":[136],"pre-pruned":[144,180],"well":[148],"default":[151],"SVMDT":[152],"pre-pruned.":[160],"because":[163],"can":[169,194],"optimally":[171],"newly":[175],"formulations":[177],"way":[188],"such":[189],"that":[190],"accuracies":[193],"significantly":[195],"improved.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
