{"id":"https://openalex.org/W2955005455","doi":"https://doi.org/10.1109/icaict.2018.8747086","title":"Comparative study of the classification models for prediction of bank telemarketing","display_name":"Comparative study of the classification models for prediction of bank telemarketing","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2955005455","doi":"https://doi.org/10.1109/icaict.2018.8747086","mag":"2955005455"},"language":"en","primary_location":{"id":"doi:10.1109/icaict.2018.8747086","doi":"https://doi.org/10.1109/icaict.2018.8747086","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaict.2018.8747086","pdf_url":null,"source":{"id":"https://openalex.org/S7407087188","display_name":"IEEE International Conference on Application of Information and Communication Technologies (AICT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 12th International Conference on Application of Information and Communication Technologies (AICT)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5003561768","display_name":"Elzhan Zeinulla","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I60559429","display_name":"Nazarbayev University","ror":"https://ror.org/052bx8q98","country_code":"KZ","type":"education","lineage":["https://openalex.org/I60559429"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Elzhan Zeinulla","raw_affiliation_strings":["Computer Science, Nazarbayev University, Astana, Kazakhstan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science, Nazarbayev University, Astana, Kazakhstan","institution_ids":["https://openalex.org/I60559429"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057972803","display_name":"Karina Bekbayeva","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I60559429","display_name":"Nazarbayev University","ror":"https://ror.org/052bx8q98","country_code":"KZ","type":"education","lineage":["https://openalex.org/I60559429"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Karina Bekbayeva","raw_affiliation_strings":["Computer Science, Nazarbayev University, Astana, Kazakhstan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science, Nazarbayev University, Astana, Kazakhstan","institution_ids":["https://openalex.org/I60559429"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020101419","display_name":"Adnan Yaz\u0131c\u0131","orcid":"https://orcid.org/0000-0001-9404-9494","observed_orcids":["https://orcid.org/0000-0001-9404-9494"]},"institutions":[{"id":"https://openalex.org/I60559429","display_name":"Nazarbayev University","ror":"https://ror.org/052bx8q98","country_code":"KZ","type":"education","lineage":["https://openalex.org/I60559429"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Adnan Yazici","raw_affiliation_strings":["Computer Science, Nazarbayev University, Astana, Kazakhstan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science, Nazarbayev University, Astana, Kazakhstan","institution_ids":["https://openalex.org/I60559429"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I60559429"],"apc_list":null,"apc_paid":null,"fwci":2.215,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.90594619,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":87,"max":95},"biblio":{"volume":"5","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9818999767303467,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9818999767303467,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.006899999920278788,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.0019000000320374966,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/customer-response-prediction","display_name":"customer response prediction","score":0.5979999899864197},{"id":"https://openalex.org/keywords/classification-model-comparison","display_name":"classification model comparison","score":0.9279999732971191},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.9769999980926514},{"id":"https://openalex.org/keywords/deep-neural-network","display_name":"deep neural network","score":0.8270000219345093},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"logistic regression","score":0.9950000047683716},{"id":"https://openalex.org/keywords/naive-bayes","display_name":"naive Bayes","score":0.984000027179718},{"id":"https://openalex.org/keywords/overfitting","display_name":"overfitting","score":0.8450000286102295},{"id":"https://openalex.org/keywords/roc-curve","display_name":"ROC curve","score":0.8220000267028809}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8756147623062134},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7151206135749817},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.6601308584213257},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6244961619377136},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5588160753250122},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5585504174232483},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.551007091999054},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5206500887870789},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5038999915122986},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.399076372385025},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22848248481750488},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.15943452715873718},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaict.2018.8747086","doi":"https://doi.org/10.1109/icaict.2018.8747086","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaict.2018.8747086","pdf_url":null,"source":{"id":"https://openalex.org/S7407087188","display_name":"IEEE International Conference on Application of Information and Communication Technologies (AICT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 12th International Conference on Application of Information and Communication Technologies (AICT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1661924774","https://openalex.org/W1663415130","https://openalex.org/W1974005842","https://openalex.org/W2014981960","https://openalex.org/W2074780813","https://openalex.org/W2097998348","https://openalex.org/W2103647733","https://openalex.org/W2130486630","https://openalex.org/W2186433969","https://openalex.org/W2259424905","https://openalex.org/W2533505830","https://openalex.org/W2533802506","https://openalex.org/W2771851444","https://openalex.org/W2911964244","https://openalex.org/W2962854379","https://openalex.org/W2990168612","https://openalex.org/W4230603309","https://openalex.org/W4241699496"],"related_works":["https://openalex.org/W4399767558","https://openalex.org/W4389048138","https://openalex.org/W4405304192","https://openalex.org/W4413249420","https://openalex.org/W4310712853","https://openalex.org/W4225316956","https://openalex.org/W7071121715","https://openalex.org/W2771851444","https://openalex.org/W4312947842","https://openalex.org/W7207869675"],"abstract_inverted_index":{"This":[0],"research":[1],"paper":[2],"has":[3,32],"evaluated":[4,34],"various":[5],"classification":[6,93],"models":[7],"for":[8,67,95],"prediction":[9,71],"of":[10,18,21,29,49,54,61,98],"bank":[11,68],"telemarketing":[12,69],"campaign":[13],"results":[14,60],"regarding":[15],"the":[16,19,22,25,47,50,55,59,62,64,91,102],"probability":[17],"subscription":[20],"customer":[23],"to":[24,58,101],"deposit.":[26],"The":[27,80],"effectiveness":[28,70],"these":[30],"algorithms":[31],"been":[33],"by":[35],"Receiving":[36],"Operator":[37],"Characteristic":[38],"(ROC)":[39],"and":[40,52,75,83,105],"Cumulative":[41],"Accuracy":[42],"Profile":[43],"(CAP)":[44],"curve":[45],"analysis,":[46],"accuracy":[48,104],"algorithm":[51],"variance":[53],"predictions.":[56],"According":[57],"research,":[63],"best":[65],"model":[66],"are":[72,86],"Random":[73],"Forest":[74],"Deep":[76],"Artificial":[77],"Neural":[78],"Network.":[79],"Logistic":[81],"Regression":[82],"Naive":[84],"Bayes":[85],"not":[87],"as":[88,90],"suitable":[89],"other":[92],"methods":[94],"this":[96],"kind":[97],"problems":[99],"due":[100],"poor":[103],"overfitting":[106],"issues.":[107]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2019-07-12T00:00:00"}