Comparative Analysis of algorithm for big data classification

Comparative Analysis of algorithm for big data classification | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative Analysis of algorithm for big data classification Shashi Pal Singh, Ritu Tiwari, Sanjeev Sharma This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3999157/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In today’s scenario where a vast amount of text, images and documents are sent and received mostly of which the data in unstructured textual form. We observe that every minute of the day a large amount of data is stored. This huge amount of data needs to be process which is impossible for human being to do it. The purpose of this comparative analysis is to reduce the classification errors using various algorithms by estimating the distribution of class by using vectors. Nowadays, to acquire meaningful, useful data from the vast variety of textual and documented data present it is necessary and viable to build techniques and algorithm better than before. Hence, in order to get interesting and needful information we use model classification, evolution and regression. The data is collected from records or created or taken from the organization to create the database then the pre-processing of data is done so that various classification algorithms can be applied and can be compared on the basis of precision, efficiency, accuracy, ROC curve and missing values and different results can be predicted to solve the problems. classification algorithms dataset text pre-processing Data Mining Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3999157","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":275922963,"identity":"7f096893-7cac-438a-8dcc-1cf2cb67afe1","order_by":0,"name":"Shashi Pal Singh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYDACCQYGZgYDBjkGhgQgz4AELcakamFgSGwAayEGyM9ufvy5oKAuvb89+eEHhoI7hLUY3DlmJj3D4HDujDPPjCUYDJ4RoUUiwYyZx+BA7gYgA8g9TITDZqR//sxjUJduIJH+jTgtDDdyDKR5DJgTDCRyiLTF4EZOGVDLYcMZZ94USyQQ6bDNn3n+1Mnzt6dv/PDhDzEOQwEJpGoYBaNgFIyCUYAdAAAkMDV0vfZ1OQAAAABJRU5ErkJggg==","orcid":"","institution":"Centre for Development of Advanced Computing","correspondingAuthor":true,"prefix":"","firstName":"Shashi","middleName":"Pal","lastName":"Singh","suffix":""},{"id":275922964,"identity":"4c60b7df-3357-4285-8e25-0f842b588a4c","order_by":1,"name":"Ritu Tiwari","email":"","orcid":"","institution":"Indian Institute of Information Technology (IIIT) Pune","correspondingAuthor":false,"prefix":"","firstName":"Ritu","middleName":"","lastName":"Tiwari","suffix":""},{"id":275922965,"identity":"06295d80-6496-4f1e-9848-760136309155","order_by":2,"name":"Sanjeev Sharma","email":"","orcid":"","institution":"Indian Institute of Information Technology (IIIT) Pune","correspondingAuthor":false,"prefix":"","firstName":"Sanjeev","middleName":"","lastName":"Sharma","suffix":""}],"badges":[],"createdAt":"2024-02-29 09:19:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3999157/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3999157/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52536118,"identity":"859a7685-d388-48c4-b46e-70c402b858d0","added_by":"auto","created_at":"2024-03-12 16:33:04","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":387369,"visible":true,"origin":"","legend":"","description":"","filename":"ComparativeClassification4.0.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3999157/v1_covered_7aebd59a-51d8-468e-87ec-dec729c9e353.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Analysis of algorithm for big data classification","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"classification algorithms, dataset text, pre-processing, Data Mining","lastPublishedDoi":"10.21203/rs.3.rs-3999157/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3999157/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"In today’s scenario where a vast amount of text, images and documents are sent and received mostly of which the data in unstructured textual form. We observe that every minute of the day a large amount of data is stored. This huge amount of data needs to be process which is impossible for human being to do it. The purpose of this comparative analysis is to reduce the classification errors using various algorithms by estimating the distribution of class by using vectors. Nowadays, to acquire meaningful, useful data from the vast variety of textual and documented data present it is necessary and viable to build techniques and algorithm better than before. Hence, in order to get interesting and needful information we use model classification, evolution and regression. The data is collected from records or created or taken from the organization to create the database then the pre-processing of data is done so that various classification algorithms can be applied and can be compared on the basis of precision, efficiency, accuracy, ROC curve and missing values and different results can be predicted to solve the problems.","manuscriptTitle":"Comparative Analysis of algorithm for big data classification","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-05 03:28:09","doi":"10.21203/rs.3.rs-3999157/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"04969fcb-c0e9-4e9e-93f9-64ffb1755fc5","owner":[],"postedDate":"March 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-12T16:27:00+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-05 03:28:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3999157","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3999157","identity":"rs-3999157","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}