LEADER 01711nam0 2200361 i 450 001 SUN0003503 005 20111020113656.861 010 $a88-02-05042-2 020 $aIT$b97 2375 100 $a20020711d1996 |0itac50 ba 101 $aita 102 $aIT 105 $a|||| ||||| 200 1 $aAtti del procedimento penale$eforma e struttura$fcontributi di Giuseppe Di Chiara ... [et al.]$gcoordinati da Enrico Marzaduri 205 $aTorino : UTET$b1996 210 $aXI$d251 p. ; 25 cm 215 $aVolume presente anche nel Fondo Tribunale. 410 1$1001SUN0003626$12001 $aGiurisprudenza sistematica di diritto processuale penale$1210 $aTorino$cUtet. 606 $aAtti processuali penali$xGiurisprudenza$2FI$3SUNC002415 620 $dTorino$3SUNL000001 676 $a345.4507$cDiritto penale. Processi. Italia$v21 702 1$aDi Chiara$b, Giuseppe$f1964- $3SUNV001565 702 1$aChiavario$b, Mario$3SUNV001632 702 1$aMarzaduri$b, Enrico$3SUNV003434 712 $aUTET$3SUNV000072$4650 801 $aIT$bSOL$c20181109$gRICA 912 $aSUN0003503 950 $aUFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI GIURISPRUDENZA$d00 CONS XVII.F.4 $e00 9205 950 $aUFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI GIURISPRUDENZA$d00 CONS XVII.F.4 bis $e00 FT 36150 995 $aUFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI GIURISPRUDENZA$h9205$kCONS XVII.F.4$op$qa 995 $aUFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI GIURISPRUDENZA$gFT$h36150$kCONS XVII.F.4 bis$op$qa 996 $aAtti del procedimento penale$9195041 997 $aUNICAMPANIA LEADER 04945nam 22006611 450 001 9910790502403321 005 20200520144314.0 010 $a1-84968-547-9 035 $a(CKB)2550000001137071 035 $a(EBL)1441770 035 $a(OCoLC)862048592 035 $a(SSID)ssj0001139609 035 $a(PQKBManifestationID)11618112 035 $a(PQKBTitleCode)TC0001139609 035 $a(PQKBWorkID)11214366 035 $a(PQKB)11484304 035 $a(Au-PeEL)EBL1441770 035 $a(CaPaEBR)ebr10789474 035 $a(CaONFJC)MIL536772 035 $a(OCoLC)869836216 035 $a(CaSebORM)9781849685467 035 $a(MiAaPQ)EBC1441770 035 $a(PPN)228042216 035 $a(EXLCZ)992550000001137071 100 $a20131207h20132013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aIBM SPSS modeler cookbook /$fKeith McCormick [and four others] 205 $a1st edition 210 1$aBirmingham :$cPackt Publishing,$d[2013] 210 4$dİ2013 215 $a1 online resource (382 p.) 300 $aIncludes index. 311 $a1-84968-546-0 311 $a1-306-05521-0 327 $a""Cover""; ""Copyright""; ""Credits""; ""Foreword""; ""About the Authors""; ""About the Reviewers""; ""www.PacktPub.com""; ""Table of Contents""; ""Preface""; ""Chapter 1: Data Understanding""; ""Introduction""; ""Using an empty aggregate to evaluate sample size ""; ""Evaluating the need to sample from the initial data""; ""Using CHAID stumps when interviewing an SME""; ""Using a single cluster K-means as an alternative to anomaly detection""; ""Using an @NULL multiple Derive to explore missing data""; ""Creating an outlier report to give to SMEs"" 327 $a""Detecting potential model instability early using the Partition node and Feature Selection""""Chapter 2: Data Preparation a??? Select""; ""Introduction""; ""Using the Feature Selection node creatively to remove, or decapitate, perfect predictors""; ""Running a Statistics node on anti-join to evaluate potential missing data""; ""Evaluating the use of sampling for speed""; ""Removing redundant variables using correlation matrices""; ""Selecting variable using the CHAID modeling node""; ""Selecting variables using the Means node"" 327 $a""Selecting variables using single-antecedent association rules""""Chapter 3: Data Preparation a??? Clean""; ""Introduction""; ""Binning scale variables to address missing data""; ""Using a full data model/partial data model approach to address missing data""; ""Imputing in-stream mean or median""; ""Imputing missing values randomly from uniform or normal distributions""; ""Using random imputation to match a variable's distribution""; ""Searching for similar records using a neural network for inexact matching""; ""Using neuro-fuzzy searching to find similar names"" 327 $a""Producing longer Soundex codes""""Chapter 4: Data Preparation a??? Construct""; ""Introduction""; ""Building transformations with multiple Derive nodes""; ""Calculating and comparing conversion rates""; ""Grouping categorical values""; ""Transforming high skew and kurtosis variables with a multiple Derive node""; ""Creating flag variables for aggregation""; ""Using Association Rules for interaction detection/feature creation""; ""Creating time-aligned cohorts""; ""Chapter 5: Data Preparation a??? Integrate and Format""; ""Introduction"" 327 $a""Speeding up merge with caching and optimization settings""""Merging a look-up table""; ""Shuffle-down (nonstandard aggregation)""; ""Cartesian product merge using key-less merge by key""; ""Multiplying out using Cartesian product merge, user source, and derive dummy""; ""Changing large numbers of variable names without scripting""; ""Parsing nonstandard dates""; ""Parsing and performing a conversion on a complex stream""; ""Sequence processing""; ""Chapter 6: Selecting and Building a Model""; ""Introduction""; ""Evaluating balancing with the Auto Classifier"" 327 $a""Building models with and without outliers"" 330 $aThis is a practical cookbook with intermediate-advanced recipes for SPSS Modeler data analysts. It is loaded with step-by-step examples explaining the process followed by the experts.If you have had some hands-on experience with IBM SPSS Modeler and now want to go deeper and take more control over your data mining process, this is the guide for you. It is ideal for practitioners who want to break into advanced analytics. 606 $aData mining 606 $aDatabase management 615 0$aData mining. 615 0$aDatabase management. 676 $a005.478 700 $aMcCormick$b Keith$0951317 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910790502403321 996 $aIBM SPSS modeler cookbook$93677608 997 $aUNINA