{"id":"https://openalex.org/W2892022696","doi":"https://doi.org/10.1145/3220267.3220282","title":"Predicting the Survivors of the Titanic Kaggle, Machine Learning From Disaster","display_name":"Predicting the Survivors of the Titanic Kaggle, Machine Learning From Disaster","publication_year":2018,"publication_date":"2018-05-02","ids":{"openalex":"https://openalex.org/W2892022696","doi":"https://doi.org/10.1145/3220267.3220282","mag":"2892022696"},"language":"en","primary_location":{"id":"doi:10.1145/3220267.3220282","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3220267.3220282","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Conference on Software and Information Engineering","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/A5111600470","display_name":"Nadine Farag","orcid":null},"institutions":[{"id":"https://openalex.org/I154023281","display_name":"British University in Egypt","ror":"https://ror.org/0066fxv63","country_code":"EG","type":"education","lineage":["https://openalex.org/I154023281"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Nadine Farag","raw_affiliation_strings":["The British University in Egypt, Cairo, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The British University in Egypt, Cairo, Egypt","institution_ids":["https://openalex.org/I154023281"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000769467","display_name":"Ghada Hassan","orcid":"https://orcid.org/0000-0001-6732-231X"},"institutions":[{"id":"https://openalex.org/I107720978","display_name":"Ain Shams University","ror":"https://ror.org/00cb9w016","country_code":"EG","type":"education","lineage":["https://openalex.org/I107720978"]},{"id":"https://openalex.org/I154023281","display_name":"British University in Egypt","ror":"https://ror.org/0066fxv63","country_code":"EG","type":"education","lineage":["https://openalex.org/I154023281"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Ghada Hassan","raw_affiliation_strings":["Ain Shams University &amp; The British University in Egypt, Cairo, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ain Shams University &amp; The British University in Egypt, Cairo, Egypt","institution_ids":["https://openalex.org/I154023281","https://openalex.org/I107720978"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.75,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.72993056,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"32","last_page":"37"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11801","display_name":"Reservoir Engineering and Simulation Methods","score":0.6158000230789185,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11801","display_name":"Reservoir Engineering and Simulation Methods","score":0.6158000230789185,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.5935999751091003,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.5333999991416931,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7799806594848633},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7019197940826416},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6960384249687195},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6786286234855652},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6006681323051453},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5658287405967712},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.49631696939468384},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.486568808555603},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.46587109565734863},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.4623139798641205},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44303229451179504},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.42627355456352234},{"id":"https://openalex.org/keywords/competition","display_name":"Competition (biology)","score":0.4207848310470581},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3067523241043091},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.24480316042900085}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7799806594848633},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7019197940826416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6960384249687195},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6786286234855652},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6006681323051453},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5658287405967712},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.49631696939468384},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.486568808555603},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.46587109565734863},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.4623139798641205},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44303229451179504},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.42627355456352234},{"id":"https://openalex.org/C91306197","wikidata":"https://www.wikidata.org/wiki/Q45767","display_name":"Competition (biology)","level":2,"score":0.4207848310470581},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3067523241043091},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.24480316042900085},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","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":1,"locations":[{"id":"doi:10.1145/3220267.3220282","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3220267.3220282","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Conference on Software and Information Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/14","display_name":"Life below water"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2488408678","https://openalex.org/W2564406132","https://openalex.org/W2735368772","https://openalex.org/W2897593054"],"related_works":["https://openalex.org/W4389954502","https://openalex.org/W2771255398","https://openalex.org/W2930428186","https://openalex.org/W3200027047","https://openalex.org/W4385770464","https://openalex.org/W3125536479","https://openalex.org/W4224262160","https://openalex.org/W3120363735","https://openalex.org/W4214820172","https://openalex.org/W2394323384"],"abstract_inverted_index":{"April":[0],"14th,":[1],"1912":[2],"was":[3],"very":[4],"unfortunate":[5],"for":[6,69,94,166],"the":[7,16,25,28,41,57,60,87,92,99,102,128,137,175,197,202],"most":[8],"powerful":[9],"ship":[10],"ever":[11],"built":[12],"at":[13],"that":[14],"time,":[15],"Titanic.":[17],"Grievously,":[18],"1503":[19],"out":[20],"of":[21,59,101,119,139,151,158,196,199],"2203":[22],"passengers":[23,104],"perished":[24],"sinking,":[26],"but":[27],"rationale":[29],"behind":[30],"survival":[31,100,198],"still":[32],"remains":[33],"a":[34,45,63,70],"question":[35],"mark.":[36],"In":[37],"efforts":[38],"to":[39,81,90,97,145,185],"study":[40],"Titanic":[42,61,88,103],"passengers;":[43],"Kaggle,":[44],"popular":[46],"data":[47,89,93,125],"science":[48],"website,":[49],"assembled":[50],"information":[51],"about":[52],"each":[53],"passenger":[54],"back":[55],"in":[56,209],"days":[58],"into":[62],"dataset,":[64],"and":[65,96,112,117,127,142,148,156,174,178],"made":[66],"it":[67],"available":[68],"competition":[71],"titled:":[72],"\"Titanic:":[73],"Machine":[74],"Learning":[75],"from":[76],"Disaster.\"":[77],"This":[78],"research":[79],"aims":[80],"use":[82],"machine":[83,143],"learning":[84,144],"techniques":[85],"on":[86,124],"analyze":[91],"classification":[95],"predict":[98],"by":[105],"using":[106],"data-mining":[107],"algorithms;":[108],"specifically":[109],"Decision":[110,189],"Trees":[111],"Na\u00efve":[113,204],"Bayes.":[114],"The":[115,130,170,188],"prediction":[116,179],"efficiency":[118],"these":[120],"algorithms":[121],"depend":[122],"greatly":[123],"analysis":[126],"model.":[129],"paper":[131],"presents":[132],"an":[133,163,167],"implementation":[134,176],"which":[135],"combines":[136],"benefits":[138],"feature":[140],"selection":[141],"accurately":[146,193],"select":[147],"distinguish":[149],"characteristics":[150],"passengers'":[152],"age,":[153],"class,":[154],"cabin,":[155],"port":[157],"embarkation":[159],"then":[160,183],"consequently":[161],"infer":[162],"authentic":[164],"model":[165],"accurate":[168],"prediction.":[169,210],"data-set":[171],"is":[172],"described":[173],"details":[177],"results":[180],"are":[181],"presented":[182],"compared":[184],"other":[186],"results.":[187],"Tree":[190],"algorithm":[191],"has":[192],"predicted":[194],"90.01%":[195],"passengers,":[200],"while":[201],"Gaussian":[203],"Bayes":[205],"witnessed":[206],"92.52%":[207],"accuracy":[208]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
