Research on Emergency Material Supplier Evaluation Method Based on Improved Filter and Random Forest
In response to the problem of poor classification performance in emergency material supplier evaluation due to subjective factors and redundant indicators,a method based on improved Filter and random forest is proposed to improve the classification and prediction performance of emergency material supplier evaluation.Utilizing the efficient computing power of the Laplace score algorithm in Filter for preliminary feature optimization,and introducing mutual information method to eliminate redundant features in this process,a random forest classifier is constructed to reduce the adverse effects caused by redundant indicators while eliminating subjective factors.Experimental data shows that this method can significantly improve the classification and prediction performance of emergency material supplier evaluation,providing a reliable basis for the rapid construction and efficient operation of emergency supply chain management.
improve Filtermutual information methodrandom forestemergency material supplierevaluation
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