LEADER 01022nam1 2200349 450 001 990006102430203316 005 20151127145555.0 035 $a000610243 035 $aUSA01000610243 035 $a(ALEPH)000610243USA01 035 $a000610243 100 $a20010711d1949----km-y0itay0103----ba 101 $aita 102 $aIT 105 $a||||||||001yy 200 1 $aStoria della letteratura romana$fOnorato Tescari 210 $aTorino [etc.]$cSocietā editrice internazionale$d1949 215 $avolumi$d22 cm 410 0$12001 461 1$1001$12001 463 \1$1001990000558590203316$12001 $a<<1.>> Dalle origini al VII secolo d.C. 606 0 $aLetteratura latina$xStoria$2BNCF 676 $a870.9 700 1$aTESCARI,$bOnorato$0161440 801 0$aIT$bsalbc$gISBD 912 $a990006102430203316 951 $aXV.9.M. 2064$bMAR$cXV.9.M. 959 $aBK 969 $aMAR 979 $aALESSANDRA$b90$c20151127$lUSA01$h1455 996 $aStoria della letteratura romana$91383588 997 $aUNISA LEADER 00903nam0-2200313---450- 001 990009431190403321 005 20110927082948.0 010 $a978-0-691-14752-9 035 $a000943119 035 $aFED01000943119 035 $a(Aleph)000943119FED01 035 $a000943119 100 $a20110923d2010----km-y0itay50------ba 101 0 $aeng 102 $aUS 105 $aa-------001yy 200 1 $aHistory lessons$ethe creation of american jewish heritage$fBeth S. Wenger 210 $aPrinceton$cPrinceton University press$d2010 215 $axiv, 282 p.$cill$d24 cm 610 0 $aEbrei$aStati Uniti d'America$aStoria 676 $a973.04924$v21$zita 700 1$aWenger,$bBeth S.$0475988 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a990009431190403321 952 $aXIV D 175$b46169$fFSPBC 959 $aFSPBC 996 $aHistory lessons$9242681 997 $aUNINA LEADER 03547nam 2200517 450 001 996320839503316 005 20230721034820.0 010 $a94-91431-46-3 035 $a(CKB)3710000000119975 035 $a(EBL)1696015 035 $a(SSID)ssj0001225084 035 $a(PQKBManifestationID)12541207 035 $a(PQKBTitleCode)TC0001225084 035 $a(PQKBWorkID)11267783 035 $a(PQKB)10690697 035 $a(MiAaPQ)EBC1696015 035 $a(EXLCZ)993710000000119975 100 $a20081002d2008 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aPaideia at play $elearning and wit in Apuleius /$fedited by Werner Riess 210 1$aGroningen :$cBarkhuis Publishing :$cGroningen University Library,$d2008. 215 $a1 online resource (326 p.) 225 1 $aAncient narrative. Supplementum,$x1568-3540 ;$v11 300 $a"This volume presents a collection of revised versions of papers originally read at the international conference "Apuleius and the second sophistic : an orator at play," which took place at the University of North Carolina at Chapel Hill on March 23-25, 2007"--P. [vii]. 311 $a90-77922-41-5 320 $aIncludes bibliographical references (pages [263]-280) and indexes. 327 $aThe sophist at play in court : Apuleius' Apology and his literary career / Stephen J. Harrison -- Legal strategy and learned display in Apuleius' Apology / James B. Rives -- Apuleius Socrates Africanus? : Apuleius' defensive play / Werner Reiss -- Homer in Apuleius' Apology / Vincent Hunink -- The "riches" of poverty : literary games with poetry in Apuleius' Luas Paupertatis (Apology 18) / Thomas D. McCreight -- Eloquentia ludens : Apuleius' Apology and the cheerful side of standing trial / Stefan Tilg -- Centaus solis fabulis : a symposiastic reading of Apuleius' novel / Maaike Zimmerman -- A festival of laughter : Lucius, Milo and Isis playing the game of Hospitium / Robert E. Vander Poppen -- Social commentary in the Metamorphoses : Apuleius' play with satire / Elizabeth M. Greene -- Playing with elegy : tales of lovers in books 1 and 2 of Apuleius' Metamorphoses / Amanda G. Mathis -- Vigilans somniabar : some narrative uses of dreams in Apuleius' Metamorphoses / David P.C. Carlisle -- Apuleian Ecphraseis : depiction at play / Niall W. Slater. 330 $aPaidea, the yearning for, and display of knowledge, reached its' height as a cultural concept in the works of the Second Sophistic, an elite literary and philosophical movement seeking to ape the style and achievements of the 5th and 4th centuries BC. A crucial element in the display of paidea was an ability to mix the witty and playful with the serious and instructive. The Second Sophistic is known as a Greek phenomenon, but these essays ask how the Latin author Apuleius fitted into this framework, and created a distinctively latin expression of paidea, focusing on the elements of playfulness 410 0$aAncient narrative.$pSupplementum ;$v11. 606 $aSecond Sophistic movement 606 $aEducation, Ancient 615 0$aSecond Sophistic movement. 615 0$aEducation, Ancient. 702 $aRiess$b Werner 712 12$aApuleius and the Second Sophistic: an Orator at Play$f(2007 :$eUniversity of North Carolina at Chapel Hill), 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996320839503316 996 $aPaideia at play$92979394 997 $aUNISA LEADER 04056nam 22005655 450 001 9910768172903321 005 20240312140702.0 010 $a981-9976-57-X 024 7 $a10.1007/978-981-99-7657-7 035 $a(MiAaPQ)EBC30979404 035 $a(Au-PeEL)EBL30979404 035 $a(CKB)29126986800041 035 $a(DE-He213)978-981-99-7657-7 035 $a(EXLCZ)9929126986800041 100 $a20231129d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDirty Data Processing for Machine Learning /$fby Zhixin Qi, Hongzhi Wang, Zejiao Dong 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (141 pages) 311 08$aPrint version: Qi, Zhixin Dirty Data Processing for Machine Learning Singapore : Springer Singapore Pte. Limited,c2024 9789819976560 327 $aChapter 1. Introduction -- Chapter 2. Impacts of Dirty Data on Classification and Clustering Models -- Chapter 3. Dirty-Data Impacts on Regression Models -- Chapter 4. Incomplete Data Classification with View-Based Decision Tree -- Chapter 5. Density-Based Clustering for Incomplete Data -- Chapter 6. Feature Selection on Inconsistent Data -- Chapter 7. Cost-Sensitive Decision Tree Induction on Dirty Data. 330 $aIn both the database and machine learning communities, data quality has become a serious issue which cannot be ignored. In this context, we refer to data with quality problems as ?dirty data.? Clearly, for a given data mining or machine learning task, dirty data in both training and test datasets can affect the accuracy of results. Accordingly, this book analyzes the impacts of dirty data and explores effective methods for dirty data processing. Although existing data cleaning methods improve data quality dramatically, the cleaning costs are still high. If we knew how dirty data affected the accuracy of machine learning models, we could clean data selectively according to the accuracy requirements instead of cleaning all dirty data, which entails substantial costs. However, no book to date has studied the impacts of dirty data on machine learning models in terms of data quality. Filling precisely this gap, the book is intended for a broad audience ranging from researchers inthe database and machine learning communities to industry practitioners. Readers will find valuable takeaway suggestions on: model selection and data cleaning; incomplete data classification with view-based decision trees; density-based clustering for incomplete data; the feature selection method, which reduces the time costs and guarantees the accuracy of machine learning models; and cost-sensitive decision tree induction approaches under different scenarios. Further, the book opens many promising avenues for the further study of dirty data processing, such as data cleaning on demand, constructing a model to predict dirty-data impacts, and integrating data quality issues into other machine learning models. Readers will be introduced to state-of-the-art dirty data processing techniques, and the latest research advances, while also finding new inspirations in this field. 606 $aArtificial intelligence$xData processing 606 $aData mining 606 $aBig data 606 $aData Science 606 $aData Mining and Knowledge Discovery 606 $aBig Data 615 0$aArtificial intelligence$xData processing. 615 0$aData mining. 615 0$aBig data. 615 14$aData Science. 615 24$aData Mining and Knowledge Discovery. 615 24$aBig Data. 676 $a005.7 700 $aQi$b Zhixin$01453413 701 $aWang$b Hongzhi$0654187 701 $aDong$b Zejiao$01453414 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910768172903321 996 $aDirty Data Processing for Machine Learning$93656032 997 $aUNINA