{"id":"https://openalex.org/W2953662356","doi":"https://doi.org/10.1109/pdgc.2018.8745727","title":"Predictive Data Modeling: Educational Data Classification and Comparative Analysis of Classifiers Using Python","display_name":"Predictive Data Modeling: Educational Data Classification and Comparative Analysis of Classifiers Using Python","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2953662356","doi":"https://doi.org/10.1109/pdgc.2018.8745727","mag":"2953662356"},"language":"en","primary_location":{"id":"doi:10.1109/pdgc.2018.8745727","doi":"https://doi.org/10.1109/pdgc.2018.8745727","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pdgc.2018.8745727","pdf_url":null,"source":{"id":"https://openalex.org/S7407089355","display_name":"International Conference on Parallel, Distributed and Grid Computing (PDGC)","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 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)","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/A5006238068","display_name":"Pratiyush Guleria","orcid":"https://orcid.org/0000-0002-5648-9226","observed_orcids":["https://orcid.org/0000-0002-5648-9226"]},"institutions":[{"id":"https://openalex.org/I904467727","display_name":"Himachal Pradesh University","ror":"https://ror.org/02s5yma07","country_code":"IN","type":"education","lineage":["https://openalex.org/I904467727"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pratiyush Guleria","raw_affiliation_strings":["Department of Computer Science, Himachal Pradesh University, Shimla, INDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Himachal Pradesh University, Shimla, INDIA","institution_ids":["https://openalex.org/I904467727"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034919798","display_name":"Manu Sood","orcid":"https://orcid.org/0000-0002-4946-9550","observed_orcids":["https://orcid.org/0000-0002-4946-9550"]},"institutions":[{"id":"https://openalex.org/I904467727","display_name":"Himachal Pradesh University","ror":"https://ror.org/02s5yma07","country_code":"IN","type":"education","lineage":["https://openalex.org/I904467727"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manu Sood","raw_affiliation_strings":["Department of Computer Science, Himachal Pradesh University, Shimla, INDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Himachal Pradesh University, Shimla, INDIA","institution_ids":["https://openalex.org/I904467727"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I904467727"],"apc_list":null,"apc_paid":null,"fwci":0.5153,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.62121212,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"740","last_page":"746"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11122","display_name":"Online Learning and Analytics","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.00019999999494757503,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.0,"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/educational-data-mining","display_name":"educational data mining","score":0.9990000128746033},{"id":"https://openalex.org/keywords/academic-performance-prediction","display_name":"student performance prediction","score":0.9169999957084656},{"id":"https://openalex.org/keywords/internal-assessment","display_name":"internal evaluation","score":0.6069999933242798},{"id":"https://openalex.org/keywords/classifier-comparison","display_name":"classifier comparison","score":0.8730000257492065},{"id":"https://openalex.org/keywords/data-visualization","display_name":"data visualization","score":0.5950000286102295},{"id":"https://openalex.org/keywords/predictive-analytics","display_name":"predictive analytics","score":0.7490000128746033},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"supervised learning","score":0.5479999780654907},{"id":"https://openalex.org/keywords/unstructured-data","display_name":"unstructured data","score":0.6079999804496765}],"concepts":[{"id":"https://openalex.org/C2777598771","wikidata":"https://www.wikidata.org/wiki/Q5341279","display_name":"Educational data mining","level":2,"score":0.7923219203948975},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7908408045768738},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.6957972049713135},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6812667846679688},{"id":"https://openalex.org/C2777648619","wikidata":"https://www.wikidata.org/wiki/Q2845208","display_name":"Learning analytics","level":2,"score":0.5836805701255798},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5738773345947266},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5689980387687683},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.4636825919151306},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.44047701358795166},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4390134811401367},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.4126928746700287},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4075008034706116},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3595716953277588},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pdgc.2018.8745727","doi":"https://doi.org/10.1109/pdgc.2018.8745727","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pdgc.2018.8745727","pdf_url":null,"source":{"id":"https://openalex.org/S7407089355","display_name":"International Conference on Parallel, Distributed and Grid Computing (PDGC)","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 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.975600004196167,"display_name":"Quality education"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1597612134","https://openalex.org/W1972057248","https://openalex.org/W1990844260","https://openalex.org/W1998407424","https://openalex.org/W2021071494","https://openalex.org/W2035388976","https://openalex.org/W2041304617","https://openalex.org/W2079777076","https://openalex.org/W2100176599","https://openalex.org/W2106717332","https://openalex.org/W2114073252","https://openalex.org/W2128906841","https://openalex.org/W2148239836","https://openalex.org/W2235992240","https://openalex.org/W2263530181","https://openalex.org/W2496617239","https://openalex.org/W2937690641","https://openalex.org/W2949537661","https://openalex.org/W2991789205","https://openalex.org/W4249450347"],"related_works":["https://openalex.org/W7098108607","https://openalex.org/W2181701379","https://openalex.org/W3183673517","https://openalex.org/W4287029911","https://openalex.org/W2890999076","https://openalex.org/W3200433398","https://openalex.org/W2138253457","https://openalex.org/W4394002297","https://openalex.org/W2930332343","https://openalex.org/W3131658353"],"abstract_inverted_index":{"Due":[0],"to":[1,56,73,77,110],"an":[2,32,140],"increase":[3,67],"in":[4,26,103,128],"the":[5,68,81,89,172,186],"number":[6],"of":[7,18,35,70,107,125,130,139,155,185,189],"data":[8,20,29,44,93,100,127],"sources":[9],"and":[10,25,53,72,85,105,116,137,152,171,183],"digital":[11],"community,":[12],"there":[13],"is":[14,95,178],"a":[15,75],"huge":[16,62],"amount":[17],"unstructured":[19,64],"at":[21],"almost":[22],"every":[23],"synergy":[24],"such":[27],"outline,":[28],"mining":[30,45,94,101],"becomes":[31],"important":[33],"field":[34],"Machine":[36,38],"Learning.":[37],"learning":[39,52,55,168],"can":[40,166],"be":[41],"used":[42],"for":[43,180],"following":[46,145],"its":[47],"two":[48],"approaches":[49],"i.e.":[50],"Supervised":[51],"Unsupervised":[54],"find":[57,74],"out":[58],"meaningful":[59],"information":[60],"from":[61,80],"accumulated":[63],"data.":[65],"To":[66],"quality":[69],"education":[71],"solution":[76],"problems":[78],"soaring":[79],"complicated":[82],"educational":[83,92,119,141],"dataset":[84,142],"contentious":[86],"environment":[87],"among":[88],"academic":[90],"institutions,":[91],"receiving":[96],"great":[97],"attention.":[98],"Educational":[99],"helps":[102],"facilitation":[104],"utilization":[106],"resources":[108],"related":[109],"student":[111],"performance,":[112],"predicting":[113],"placement":[114],"results":[115,154],"finding":[117],"new":[118],"trends.":[120],"In":[121],"this":[122],"paper,":[123],"classification":[124,149,184],"student's":[126],"terms":[129],"internal":[131],"assessment":[132],"given":[133],"by":[134],"faculty":[135],"members":[136],"visualization":[138],"using":[143,163],"Python":[144],"multiple":[146],"Data":[147],"based":[148],"prediction":[150],"models":[151,157,162],"comparative":[153],"classifier":[156,161],"are":[158,169],"performed.":[159],"The":[160],"python":[164],"which":[165],"transform":[167],"compared":[170],"model":[173],"having":[174],"best":[175],"accuracy":[176],"measure":[177],"considered":[179],"predictive":[181],"analytics":[182],"overall":[187],"performance":[188],"class.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2019-07-12T00:00:00"}