LEADER 00820nam0-22002891i-450- 001 990000539870403321 005 20001010 035 $a000053987 035 $aFED01000053987 035 $a(Aleph)000053987FED01 035 $a000053987 100 $a20001010d--------km-y0itay50------ba 101 0 $aita 105 $ay-------001yy 200 1 $aTracciati grafici di carena e stabilitā delle navi$fGiovanni Calarco 210 $aGenova$cBriano$ds.d. 215 $a18 cm$d159 p. 300 $ain copertina c'č il sommario 700 1$aCalarco,$bGiovanni$029123 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990000539870403321 952 $a05 AN 25 44$b762$fDININ 959 $aDININ 996 $aTracciati grafici di carena e stabilitā delle navi$9329473 997 $aUNINA DB $aING01 LEADER 01846nam 2200373 450 001 9910172607403321 005 20230420154142.0 010 $a1-5090-6597-0 035 $a(CKB)3710000001362013 035 $a(NjHacI)993710000001362013 035 $a(EXLCZ)993710000001362013 100 $a20230420d2017 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$a2017 IEEE Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE) /$fInstitute of Electrical and Electronics Engineers (IEEE) 210 1$aPiscataway, New Jersey :$cInstitute of Electrical and Electronics Engineers (IEEE),$d2017. 215 $a1 online resource (various pagings) $cillustrations 311 $a1-5090-6598-9 330 $aThe aim of the workshop is to provide a forum for researchers and practitioners to present and discuss new ideas, trends and results concerning applying ML to software quality evaluation We expect that the workshop will help in (1) validation of existing and exploring new applications of ML, (2) comparing their efficiency and effectiveness, both among other automated approaches and the human judgment, and (3) adapting ML approaches already used in other areas of science. 517 $a2017 IEEE Workshop on Machine Learning Techniques for Software Quality Evaluation 606 $aComputer software$xEvaluation$vCongresses 606 $aMachine learning$vCongresses 615 0$aComputer software$xEvaluation 615 0$aMachine learning 676 $a005 801 0$bNjHacI 801 1$bNjHacl 906 $aPROCEEDING 912 $a9910172607403321 996 $a2017 IEEE Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE)$92509045 997 $aUNINA LEADER 01048nam0 22002651i 450 001 RML0239594 005 20231121125706.0 100 $a20121121d1998 ||||0itac50 ba 101 | $aita 102 $ait 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $a˜Lo œsviluppo di nuovi prodotti$eteoria e analisi empiriche in una prospettiva cognitiva$fSandro Castaldo$gGianmario Verona 210 $aMilano $cEGEA $dc1998 215 $a314 p.$cfig., tab.$d24 cm 700 1$aCASTALDO$b, Sandro$3RMLV153173$089522 701 1$aVERONA$b, Gianmario$3RMLV153172$089523 801 3$aIT$bIT-01$c20121121 850 $aIT-FR0098 899 $aBiblioteca Area Giuridico Economica$bFR0098 912 $aRML0239594 950 0$aBiblioteca Area Giuridico Economica$d 53IMP 26 201$e 53VM 0000085785 VMB A4 barcode:ECO009012. - Inventario:4655. - Fondo:Sala consultazioneVM$fA $h19981111$i20121204 977 $a 53 996 $aSviluppo di nuovi prodotti$965135 997 $aUNICAS