LEADER 00679nam0-2200241 --450 001 9910838600203321 005 20240319092255.0 100 $a20240315d1991----kmuy0itay5050 ba 101 0 $aita 102 $aIT 105 $a 001yy 200 1 $aL'Italia del risorgimento$fFulvio Tessitore 210 $a[S l.]$cGuida Editori$d1991 215 $aP. 498-500$d22 cm 300 $aEstratto da : Prospettive settanta 700 1$aTessitore,$bFulvio$04713 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aLG 912 $a9910838600203321 952 $aDFT OPUSC. 18 (09)$b2024/2061$fFLFBC 959 $aFLFBC 996 $aL'Italia del risorgimento$94144996 997 $aUNINA LEADER 01680nam 22004213 450 001 9911031637903321 005 20250904081900.0 010 $a3-032-03876-6 035 $a(MiAaPQ)EBC32276263 035 $a(Au-PeEL)EBL32276263 035 $a(CKB)40861148100041 035 $a(EXLCZ)9940861148100041 100 $a20250904d2025 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning and Clustering for a Sustainable Future $eApplications in Engineering and Environmental Science 205 $a1st ed. 210 1$aCham :$cSpringer,$d2025. 210 4$d©2025. 215 $a1 online resource (392 pages) 225 1 $aStudies in Computational Intelligence Series ;$vv.1233 311 08$a3-032-03875-8 330 $aThis book explores cutting-edge machine learning and clustering techniques to tackle critical challenges in engineering, environmental science, and sustainability.The book provides an in-depth examination of clustering methodologies, covering unsupervised and supervised techniques, data preprocessing, distance metrics, and cluster validation. 410 0$aStudies in Computational Intelligence Series 700 $aRaya-Tapia$b Alma Yunuen$01851465 701 $aLópez-Flores$b Francisco Javier$01851466 701 $aRamírez-Márquez$b César$01738153 701 $aPonce-Ortega$b José María$01228143 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911031637903321 996 $aMachine Learning and Clustering for a Sustainable Future$94445268 997 $aUNINA