LEADER 00980nam0-22003011i-450- 001 990001801350403321 005 20021010 035 $a000180135 035 $aFED01000180135 035 $a(Aleph)000180135FED01 035 $a000180135 100 $a20021010d--------km-y0itay50------ba 101 0 $aita 200 1 $a<>difesa di Napoli dalle insidie del fuoco e di altri disastri in relazione all' odierna riordinazione dei pubblici servizi$fAchille Mollo. 210 $aNapoli$cTip. Giannini$d1902. 215 $a32 p.$d22 cm 610 0 $aServizi pubblici 610 0 $aNapoli 676 $a363.6 700 1$aMollo,$bAchille$079066 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990001801350403321 952 $a60 DONO COMES 5/11$b37730$fFAGBC 959 $aFAGBC 996 $aDifesa di Napoli dalle insidie del fuoco e di altri disastri in relazione all' odierna riordinazione dei pubblici servizi$9411354 997 $aUNINA DB $aING01 LEADER 01844nam 2200373 450 001 996280186703316 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 $a996280186703316 996 $a2017 IEEE Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE)$92509045 997 $aUNISA