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- W3180892401 abstract "In this paper, company investment value evaluation models are established based on comprehensive company information. After data mining and extracting a set of 436 feature parameters, an optimal subset of features is obtained by dimension reduction through tree-based feature selection, followed by the 5-fold cross-validation using XGBoost and LightGBM models. The results show that the Root-Mean-Square Error (RMSE) reached 3.098 and 3.059, respectively. In order to further improve the stability and generalization capability, Bayesian Ridge Regression has been used to train a stacking model based on the XGBoost and LightGBM models. The corresponding RMSE is up to 3.047. Finally, the importance of different features to the LightGBM model is analysed." @default.
- W3180892401 created "2021-07-19" @default.
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- W3180892401 date "2020-01-01" @default.
- W3180892401 modified "2023-09-27" @default.
- W3180892401 title "Evaluation of company investment value based on machine learning" @default.
- W3180892401 hasPublicationYear "2020" @default.
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