{"id":"https://openalex.org/W2772624523","doi":"https://doi.org/10.1109/icacci.2017.8126052","title":"Abnormality prediction in high dimensional dataset among semi supervised learning approaches","display_name":"Abnormality prediction in high dimensional dataset among semi supervised learning approaches","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2772624523","doi":"https://doi.org/10.1109/icacci.2017.8126052","mag":"2772624523"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2017.8126052","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2017.8126052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5032085794","display_name":"Aiswarya Manghat","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Aiswarya Manghat","raw_affiliation_strings":["Dept of Computer Science and Engineering, Amritapuri Amrita Vishwa Vidyapeetham Amrita University, India"],"affiliations":[{"raw_affiliation_string":"Dept of Computer Science and Engineering, Amritapuri Amrita Vishwa Vidyapeetham Amrita University, India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065330673","display_name":"Asha Ashok","orcid":"https://orcid.org/0000-0002-0881-8312"},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Asha Ashok","raw_affiliation_strings":["Dept of Computer Science and Engineering, Amritapuri Amrita Vishwa Vidyapeetham Amrita University, India"],"affiliations":[{"raw_affiliation_string":"Dept of Computer Science and Engineering, Amritapuri Amrita Vishwa Vidyapeetham Amrita University, India","institution_ids":["https://openalex.org/I81556334"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5032085794"],"corresponding_institution_ids":["https://openalex.org/I81556334"],"apc_list":null,"apc_paid":null,"fwci":0.39,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.71843488,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"3","issue":null,"first_page":"1494","last_page":"1494"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9883000254631042,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7460712194442749},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7240133881568909},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7034225463867188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6842641830444336},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6471151113510132},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6359259486198425},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.611451268196106},{"id":"https://openalex.org/keywords/abnormality","display_name":"Abnormality","score":0.5434901118278503},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5327800512313843},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4987943172454834},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4863913357257843},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4420505166053772},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4332895874977112},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.4246445298194885},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35061201453208923},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1597588062286377}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7460712194442749},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7240133881568909},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7034225463867188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6842641830444336},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6471151113510132},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6359259486198425},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.611451268196106},{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.5434901118278503},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5327800512313843},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4987943172454834},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4863913357257843},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4420505166053772},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4332895874977112},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.4246445298194885},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35061201453208923},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1597588062286377},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icacci.2017.8126052","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2017.8126052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6399999856948853,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1924178503","https://openalex.org/W2032620230","https://openalex.org/W2130845021","https://openalex.org/W2131105131","https://openalex.org/W2147331788","https://openalex.org/W2342529049","https://openalex.org/W2548858661","https://openalex.org/W2548965762","https://openalex.org/W2678934292","https://openalex.org/W4211219292","https://openalex.org/W6739612070"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W2114217318","https://openalex.org/W2794812819","https://openalex.org/W3147024994","https://openalex.org/W2587881214","https://openalex.org/W3104072235","https://openalex.org/W2063246903","https://openalex.org/W2374055396"],"abstract_inverted_index":{"Abnormality":[0],"or":[1],"inconsistency":[2],"detection":[3],"within":[4,91],"a":[5,12,26],"data":[6,18],"is":[7,64,77,94],"an":[8],"attempt":[9],"to":[10,40,67],"make":[11],"distinction":[13],"between":[14],"usual":[15],"and":[16,113,127,137],"exceptional":[17],"instances.":[19],"In":[20],"this":[21],"paper,":[22],"we":[23],"have":[24],"proposed":[25],"novel":[27],"methodAbnormality":[28],"Prediction":[29],"in":[30,131],"High":[31],"Dimensional":[32],"Dataset":[33],"among":[34],"Semi":[35],"Supervised":[36],"Learning":[37],"approaches":[38,50],"(AP-HDD-SSL)":[39],"match":[41],"the":[42,80,85,92,116,146],"efficiencies":[43],"of":[44,133],"different":[45],"semi":[46],"supervised":[47],"machine":[48],"learning":[49,98],"using":[51,69],"high":[52],"dimensional":[53],"KDD":[54,128],"CUP":[55],"99":[56,130],"dataset.":[57],"The":[58,89,121],"pre-processing":[59,81],"phase":[60,82],"with":[61,75,96,115,124,143],"dimensionality":[62],"diminution":[63],"done":[65,95],"prior":[66],"clustering":[68],"RFE":[70],"(Random":[71],"Forest":[72],"Ensemble).":[73],"Clustering":[74],"k-Means":[76],"initiated":[78],"after":[79],"for":[83],"storing":[84],"most":[86],"anomalous":[87],"cluster.":[88],"classification":[90],"cluster":[93],"semi-supervised":[97],"approaches:":[99],"k-Nearest":[100],"Neighbour":[101],"(k-NN),":[102],"Linear":[103],"Discriminant":[104],"Analysis":[105],"(LDA),":[106],"Support":[107],"Vector":[108],"Machine-RFE(SVM-RFE),":[109],"that":[110,141],"are":[111],"analysed":[112],"compared":[114],"existing":[117],"Over":[118],"Sampling-PCA(os-PCA)":[119],"method.":[120],"comparison":[122],"results":[123],"Pima":[125],"Indian":[126],"cup":[129],"terms":[132],"Accuracy,":[134],"Detection":[135],"Rate":[136],"AUC":[138],"scores":[139],"summarizes":[140],"AP-HDD-SSL":[142],"SVM-RFE":[144],"outranked":[145],"other":[147],"approaches.":[148]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
