Using Rule-Based Machine Learning Method in a Hierarchical Framework Using Economic Performance of Companies
摘要
The article discusses important aspects of bankruptcy prediction, including early risk detection and informed financial decision making. An automated decision tree learning method can efficiently analyze multiple economic indicators, automatically identify key factors, and thus improve the accuracy and interpretability of predictions. This research approach can be a valuable tool for investors, lenders and managers, helping them to reduce financial risks and ensure the financial stability of companies. The article aims to expand the understanding of the impact of economic factors on bankruptcy and to propose innovative methods for analyzing data to make informed decisions.