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Decision tree combined with neural networks for financial forecast

机译:决策树结合神经网络进行财务预测

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In this article I would like to introduce a hybrid adaptive method. There is wide range of financial forecasts. This method is focusing on the economical default forecast, but the method can be used generally for other financial forecasts as well, for example for calculating the Value at Risk. This hybrid method is combined by two classical adaptive methods: the decision trees and the artificial neural networks. In this article I will show the structure of the hybrid method, the problems which occurred during the construction of the model and the solutions for the problems. I will show the results of the model and compare them with the results of another financial default forecast model. I will analyse the results and the reliability of the method and I will show how the parameters can influence the reliability of the results
机译:在本文中,我想介绍一种混合自适应方法。财务预测范围很广。此方法侧重于经济违约预测,但该方法通常也可用于其他财务预测,例如用于计算风险价值。该混合方法通过两种经典的自适应方法进行组合:决策树和人工神经网络。在本文中,我将展示混合方法的结构,模型构建过程中出现的问题以及问题的解决方案。我将显示模型的结果,并将其与另一个财务违约预测模型的结果进行比较。我将分析结果和方法的可靠性,并说明参数如何影响结果的可靠性

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