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Control Ore Processing Quality Based on Xgboost Machine Learning Algorithm

Published • Apr 1, 2023
NobleIDNI5P09W83R72S53
Authors:
Zibin Bi
,
Chenxi Fu
,
Junyi Zhu

Abstract

In this paper, we study the problem of quality control of ore processing, using xgboost machine learning algorithm of sklearn module in python, sample interpolation method, 011 minimization loss model and confusion matrix to build xgboost regression prediction model and classification prediction mod...

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