LEADER 00905nam0-22003131i-450- 001 990001076490403321 035 $a000107649 035 $aFED01000107649 035 $a(Aleph)000107649FED01 035 $a000107649 100 $a20000920d1971----km-y0itay50------ba 101 0 $aeng 200 1 $aBanach algebras and several complex variables$fJohn Wermer 210 $aChicago$cMarkham$d1971 610 0 $aCalcolo delle variazioni 610 0 $aDifferenze finite 610 0 $aIntegrali di fourier 610 0 $aTrasformazioni di fourier e laplace 610 0 $aFunzioni di variabile complessa 676 $a517.4//517.9 700 1$aWermer,$bJohn$041550 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990001076490403321 952 $a16-042$b8380$fFI1 959 $aFI1 996 $aBanach algebras and several complex variables$979348 997 $aUNINA DB $aING01 LEADER 04086nam 22006375 450 001 9910255003403321 005 20220623195036.0 010 $a3-319-46762-X 024 7 $a10.1007/978-3-319-46762-7 035 $a(CKB)3710000000981146 035 $a(DE-He213)978-3-319-46762-7 035 $a(MiAaPQ)EBC5589163 035 $a(PPN)19714117X 035 $a(EXLCZ)993710000000981146 100 $a20161107d2016 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 13$aAn Introduction to Data Analysis using Aggregation Functions in R /$fby Simon James 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (X, 199 p. 29 illus., 20 illus. in color.) 311 $a3-319-46761-1 327 $aAggregating data with averaging functions -- Transforming data -- Weighted averaging -- Averaging with interaction -- Fitting aggregation functions to empirical data -- Solutions. 330 $aThis textbook helps future data analysts comprehend aggregation function theory and methods in an accessible way, focusing on a fundamental understanding of the data and summarization tools. Offering a broad overview of recent trends in aggregation research, it complements any study in statistical or machine learning techniques. Readers will learn how to program key functions in R without obtaining an extensive programming background. Sections of the textbook cover background information and context, aggregating data with averaging functions, power means, and weighted averages including the Borda count. It explains how to transform data using normalization or scaling and standardization, as well as log, polynomial, and rank transforms. The section on averaging with interaction introduces OWS functions and the Choquet integral, simple functions that allow the handling of non-independent inputs. The final chapters examine software analysis with an emphasis on parameter identification rather than technical aspects. This textbook is designed for students studying computer science or business who are interested in tools for summarizing and interpreting data, without requiring a strong mathematical background. It is also suitable for those working on sophisticated data science techniques who seek a better conception of fundamental data aggregation. Solutions to the practice questions are included in the textbook. 606 $aArtificial intelligence 606 $aStatistics 606 $aApplied mathematics 606 $aEngineering mathematics 606 $aComputer science?Mathematics 606 $aR (Computer program language) 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020 606 $aApplications of Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M13003 606 $aMathematics of Computing$3https://scigraph.springernature.com/ontologies/product-market-codes/I17001 615 0$aArtificial intelligence. 615 0$aStatistics. 615 0$aApplied mathematics. 615 0$aEngineering mathematics. 615 0$aComputer science?Mathematics. 615 0$aR (Computer program language) 615 14$aArtificial Intelligence. 615 24$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aApplications of Mathematics. 615 24$aMathematics of Computing. 676 $a519.50285 700 $aJames$b Simon$4aut$4http://id.loc.gov/vocabulary/relators/aut$0121029 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910255003403321 996 $aAn Introduction to Data Analysis using Aggregation Functions in R$92289017 997 $aUNINA