Primary Study on Deep Tree-like Neural Networks
| Autor: | Chun-Ying Li, 李俊穎 |
|---|---|
| Rok vydání: | 2019 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 107 Decision tree is a handy and useful tool for statistical analysis. With relatively large data, it may mine some relatively complicated structure in the data, which may not be revealed using the traditional statistical methods. Moreover, it may uncover relatively important input variables among all input variables. Based on the aforementioned advantages of the decision tree, the proposed deep tree-like neural networks mimic the architecture of the relevant decision trees, and the input variables are determined mostly by decision trees. Some real-world datasets will be used to compare the performances of the proposed tree-like neural networks and the standard densely connected neural networks. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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