Tree Label Reconstruction from Root to End Node Value: A Deep Learning Approach. This study presents a new algorithm for reconstructing the tree label of a given dataset, specifically focusing on end nodes (leaf nodes) as they contain important information. The proposed method utilizes deep learning techniques for predicting node labels accurately, enabling efficient and accurate extraction of leaf-level information from complex data structures.
This paper explores the use of deep neural networks to enhance data retrieval processes in tree-based datasets by predicting node values at the end of each branch, facilitating more comprehensive analysis and improving overall accuracy. The approach is particularly useful in scenarios where traditional methods may struggle due to the complexity of tree structures.
