cugbczg/Machine-Learning-to-train-models-tracing-fluids-in-LIPs: v.2.0.0

Random forest (RF) is employed trace the role of fluids in the generation of the early Permian Tarim large igneous province (LIP) in northwestern China. Training data were extracted from the GEOROC (http://georoc.mpch-mainz.gwdg.de/georoc/) and PetDB (https://search.earthchem.org/) databases involving global island-arc basalts (IAB), mid-oceanic ridge basalts (MORB) and OIB to establish the predictive models. BASALT_part1-8, earthchem_download_76508--major element and earthchem_download_84755--trace element are selected data before cleaning. Primary code includes training and testing parts. Firstly, train models based on RF model using 10624 basalt samples, comprising 6239 IAB samples, 3329 OIB samples, and 1056 MORB samples. Secondly, basaltic samples were tested to yield the prediction results. Tarim data for test before cleaning is the whole compilation of geochemical elements data before data clean for the basalts from Tarim large igneous province and Central Asian Orogenic Belt.