The growth of the online data provides the user a access to information on the Internet but also creates the challenges to obtain the valuable knowledge. In this paper we focus on news text classification, which is me...
详细信息
ISBN:
(纸本)9781479942749
The growth of the online data provides the user a access to information on the Internet but also creates the challenges to obtain the valuable knowledge. In this paper we focus on news text classification, which is meaningful for information provider to organize and display the news but also for the users to reach the valuable information easily. A hierarchy method based on LDA and SVM is proposed to accomplish this task and several experiments are conducted to evaluate our method. The results show that our method is promising in text classification problems.
Misclassification minimization is an important and interesting topic in classification problem. Obviously, exploring the solution for this topic will benefit to many real life problems, such as credit card clients cla...
详细信息
ISBN:
(纸本)9781479942749
Misclassification minimization is an important and interesting topic in classification problem. Obviously, exploring the solution for this topic will benefit to many real life problems, such as credit card clients classification. This paper focuses on misclassification minimization based on multiple criteria linear programming (MCLP), proposing two different schemes to minimize the number of misclassified points in original MCLP. Especially, the complementarity is used to construct the first scheme and linear approximation technique is applied to solve it. Furthermore, successive linearization algorithm (SLA) is employed to achieve minimization the second scheme. Finally, numerical experiment tests the effect of this idea.
Misclassification minimization is an important and interesting topic in classification problem. Obviously, exploring the solution for this topic will benefit to many real life problems, such as credit card clients cla...
详细信息
Misclassification minimization is an important and interesting topic in classification problem. Obviously, exploring the solution for this topic will benefit to many real life problems, such as credit card clients classification. This paper focuses on misclassification minimization based on multiple criteria linear programming (MCLP), proposing two different schemes to minimize the number of misclassified points in original MCLP. Especially, the complementarity is used to construct the first scheme and linear approximation technique is applied to solve it. Furthermore, successive linearization algorithm (SLA) is employed to achieve minimization the second scheme. Finally, numerical experiment tests the effect of this idea.
This paper highlights the importance of measuring systemic risk of commercial banks. Conditional Value-at-Risk (CoVaR) is used to measure the degree of "risk externalities" that a specific bank contributes t...
详细信息
ISBN:
(纸本)9781479942749
This paper highlights the importance of measuring systemic risk of commercial banks. Conditional Value-at-Risk (CoVaR) is used to measure the degree of "risk externalities" that a specific bank contributes to the whole banking system. Our analysis not only presents current levels of systemic risk of individual banks but also the changes with time passes. There is some evidence that larger banks contribute more to systemic risk, but size is far from being a dominant factor. We further explore to use some determinant balance-sheet factors to predict forward CoVaR for regulatory purpose. We extend modified Support Vector Regression (SVR) specifically for panel data, and apply the new model to predict systemic risk of commercial banks. The results show that the model is suitable for this problem.
He growth of the online data provides the user a access to information on the Internet but also creates the challenges to obtain the valuable knowledge. In this paper we focus on news text classification, which is mea...
详细信息
ISBN:
(纸本)9781479942732
He growth of the online data provides the user a access to information on the Internet but also creates the challenges to obtain the valuable knowledge. In this paper we focus on news text classification, which is meaningful for information provider to organize and display the news but also for the users to reach the valuable information easily. A hierarchy method based on LDA and SVM is proposed to accomplish this task and several experiments are conducted to evaluate our method. The results show that our method is promising in text classification problems.
This paper highlights the importance of measuring systemic risk of commercial banks. Conditional Value-at-Risk (CoVaR) is used to measure the degree of "risk externalities" that a specific bank contributes t...
详细信息
ISBN:
(纸本)9781479942732
This paper highlights the importance of measuring systemic risk of commercial banks. Conditional Value-at-Risk (CoVaR) is used to measure the degree of "risk externalities" that a specific bank contributes to the whole banking system. Our analysis not only presents current levels of systemic risk of individual banks but also the changes with time passes. There is some evidence that larger banks contribute more to systemic risk, but size is far from being a dominant factor. We further explore to use some determinant balance-sheet factors to predict forward CoVaR for regulatory purpose. We extend modified Support Vector Regression (SVR) specifically for panel data, and apply the new model to predict systemic risk of commercial banks. The results show that the model is suitable for this problem.
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