0bb8e4781e1d2b74d5435bfb197b399f Min_a2023v13n7p861.pdf f2f922ccbd439ef38c06383da74e37d4ade0963b Min_a2023v13n7p861.pdf 7441690ce4ce9ecacacad60039b0e3db431d5bf4092a682a2dc12f18dd10e766 Min_a2023v13n7p861.pdf Title: Supervised Machine Learning Algorithms to Discriminate Two Similar Marble Varieties, a Case Study Subject: A multi-analytical approach is usually applied in provenance studies of archaeological marbles. However, for very similar marble varieties, additional techniques and approaches are required. This paper uses a case study to illustrate this with two Catalan marble districts (Gualba and Ceret) and three sets of archaeological marbles. The common multi-method approach is unable to discriminate between the two districts, and such distinction is only partially glimpsed using unsupervised multivariate data analyses on a transformed geochemical dataset of reference samples. In contrast, several supervised classification models have been successfully trained to discriminate between the quarries without any special data transformation. All the trained models agree to assign the three sets of archaeological samples to the Gualba quarry district. Additional outcomes of the paper are a comprehensive archaeometric characterization of the little-known marbles of Gualba and Ceret and the first archaeometrically supported evidence of the use of Gualba marble during Roman and Medieval times. Keywords: marble; provenance studies; supervised methods; machine learning; clustering; XRF; heritage science Author: Lluís Casas, Anna Anglisano, Roberta Di Febo, Berta Pedreño and Ignasi Queralt Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Mon Jun 26 09:42:06 2023 CEST ModDate: Mon Jun 26 09:49:04 2023 CEST Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 24 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 24095659 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- ZFZIVO+VnURWPalladioL Type 1 Custom yes yes no 10 0 XKBZNC+URWPalladioL-Bold Type 1 Custom yes yes no 15 0 KULEAK+URWPalladioL-Roma Type 1 Custom yes yes no 20 0 MLYIUQ+URWPalladioL-Ital Type 1 Custom yes yes no 24 0 NKXLQD+EURM10 Type 1 Builtin yes yes no 28 0 WLENKM+VnURWPalladioL-Bold Type 1 Custom yes yes no 32 0 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and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 696 FreeObjects: 1 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: section.1 Item: Title: Materials and Methods Destination: section.2 Children: Item: Title: Archaeological Samples Destination: subsection.2.1 Children: Item: Title: The City Walls of Gerunda (Girona) Destination: subsubsection.2.1.1 Item: Title: The Cloister of Saint Saviour’s Monastery (Breda) Destination: subsubsection.2.1.2 Item: Title: The Inner Bailey of Montsoriu Castle Destination: subsubsection.2.1.3 Item: Title: Quarry Samples Destination: subsection.2.2 Children: Item: Title: Gualba Marbles Destination: subsubsection.2.2.1 Item: Title: Ceret Marbles Destination: subsubsection.2.2.2 Item: Title: Methods Destination: subsection.2.3 Children: Item: Title: Experimental Methods Destination: subsubsection.2.3.1 Item: Title: Statistical Methods Destination: subsubsection.2.3.2 Item: Title: Results and Discussion Destination: section.3 Children: Item: Title: Petrography Destination: subsection.3.1 Children: Item: Title: Quarry Marbles Destination: subsubsection.3.1.1 Item: Title: Archaeological Marbles Destination: subsubsection.3.1.2 Item: Title: Cathodoluminescence Destination: subsection.3.2 Item: Title: Stable Isotopes Destination: subsection.3.3 Children: Item: Title: Quarry Marbles Destination: subsubsection.3.3.1 Item: Title: Archaeological Marbles Destination: subsubsection.3.3.2 Item: Title: Energy Dispersive X-ray Fluorescence (EDXRF) and Unsupervised Multivariate Data Analysis (MDA) Destination: subsection.3.4 Item: Title: Supervised Machine Learning Classification Models Destination: subsection.3.5 Children: Item: Title: Model Train and Test Destination: subsubsection.3.5.1 Item: Title: Class Prediction Destination: subsubsection.3.5.2 Item: Title: Conclusions Destination: section.4 Item: Title: References Destination: section.A. Info: Title: Supervised Machine Learning Algorithms to Discriminate Two Similar Marble Varieties, a Case Study Author: Lluís Casas, Anna Anglisano, Roberta Di Febo, Berta Pedreño and Ignasi Queralt Subject: A multi-analytical approach is usually applied in provenance studies of archaeological marbles. However, for very similar marble varieties, additional techniques and approaches are required. This paper uses a case study to illustrate this with two Catalan marble districts (Gualba and Ceret) and three sets of archaeological marbles. The common multi-method approach is unable to discriminate between the two districts, and such distinction is only partially glimpsed using unsupervised multivariate data analyses on a transformed geochemical dataset of reference samples. In contrast, several supervised classification models have been successfully trained to discriminate between the quarries without any special data transformation. All the trained models agree to assign the three sets of archaeological samples to the Gualba quarry district. Additional outcomes of the paper are a comprehensive archaeometric characterization of the little-known marbles of Gualba and Ceret and the first archaeometrically supported evidence of the use of Gualba marble during Roman and Medieval times. 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