This paper presents a new negative judgment matrix that combines the advantages of the reciprocal judgment matrix and the fuzzy complementary judgment matrix, and then puts forth the properties of this new matrix. In ...This paper presents a new negative judgment matrix that combines the advantages of the reciprocal judgment matrix and the fuzzy complementary judgment matrix, and then puts forth the properties of this new matrix. In view of these properties, this paper derives a clear sequencing formula for the new negative judgment matrix, which improves the sequencing principle of AHP. Finally, this new method is applied to personal credit evaluation to show its advantages of conciseness and swiftness.展开更多
How to establish a personal credit evaluation model with both interpretability and high prediction accuracy is an essential task in the credit risk management of commercial banks.To realize interpretable personal cred...How to establish a personal credit evaluation model with both interpretability and high prediction accuracy is an essential task in the credit risk management of commercial banks.To realize interpretable personal credit evaluation with high accuracy,it proposes an interpretable personal credit evaluation model DTONN(i.e.,Decision Tree extracted from Neural Network)that combines the interpretability of decision tree and the high prediction accuracy of neural network.Significant features were selected from raw features by a decision tree,and a four-layer neural network was constructed to predict personal credit by using the selected features.Therefore,the accurate credit evaluation was made through the neural network and associated decision process was intelligibly displayed in the form of a decision tree.In the experiments,DTONN was compared with four personal credit evaluation models:decision tree,neural network,support vector machine,and logistic regression,on giveme-some-credit credit dataset.The experimental results show that our proposed model is state-of-the-art both on the accuracy and interpretability.展开更多
文摘This paper presents a new negative judgment matrix that combines the advantages of the reciprocal judgment matrix and the fuzzy complementary judgment matrix, and then puts forth the properties of this new matrix. In view of these properties, this paper derives a clear sequencing formula for the new negative judgment matrix, which improves the sequencing principle of AHP. Finally, this new method is applied to personal credit evaluation to show its advantages of conciseness and swiftness.
基金National Defense Science and Technology Innovation Special Zone Project(No.18-163-11-ZT-002-045-04).
文摘How to establish a personal credit evaluation model with both interpretability and high prediction accuracy is an essential task in the credit risk management of commercial banks.To realize interpretable personal credit evaluation with high accuracy,it proposes an interpretable personal credit evaluation model DTONN(i.e.,Decision Tree extracted from Neural Network)that combines the interpretability of decision tree and the high prediction accuracy of neural network.Significant features were selected from raw features by a decision tree,and a four-layer neural network was constructed to predict personal credit by using the selected features.Therefore,the accurate credit evaluation was made through the neural network and associated decision process was intelligibly displayed in the form of a decision tree.In the experiments,DTONN was compared with four personal credit evaluation models:decision tree,neural network,support vector machine,and logistic regression,on giveme-some-credit credit dataset.The experimental results show that our proposed model is state-of-the-art both on the accuracy and interpretability.
