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    A Data-Driven Approach for Lithology Identification Based on Parameter-Optimized Ensemble Learning by Zhixue Sun, Baosheng Jiang, Xiangling Li, Jikang Li, Kang Xiao

    Published 2020-07-01
    “…The identification of underground formation lithology can serve as a basis for petroleum exploration and development. This study integrates Extreme Gradient Boosting (XGBoost) with Bayesian Optimization (BO) for formation lithology identification and comprehensively evaluated the performance of the proposed classifier based on the metrics of the confusion matrix, precision, recall, F1-score and the area under the receiver operating characteristic curve (AUC). …”
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