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| Title: | 邏輯斯迴歸與隨機森林預測能力比較探討
A Comparative Study of Predictive Performance between Logistic Regression and Random Forest |
| Authors: | 陳柏勳
Chen, Bo-Xun |
| Contributors: | 黃子銘
Huang, Tzee-Ming
陳柏勳
Chen, Bo-Xun |
| Keywords: | 邏輯斯迴歸
隨機森林
B-spline
Logistic regression
Random forest |
| Date: | 2020 |
| Issue Date: | 2021-02-01 13:59:39 (UTC+8) |
| Abstract: | 在針對二元變數的預測中，邏輯斯迴歸往往會被選為比較的對象之一。而在許多預測的競賽之中，邏輯斯迴歸所產生的預測結果，往往差強人意。因此本研究將針對邏輯斯迴歸與隨機森林比較的問題進行探討。在本研究中，對於邏輯斯迴歸之所以會輸於隨機森林表現的原因歸結在模型複雜度，並針對此點去設計模擬比較傳統邏輯斯迴歸、以 additive Bspline 和 tensor product Bspline 為基底的邏輯斯迴歸模型以及隨機森林四個模型，最終在模擬的設定下，結果得出後三個模型僅具有些微差距，而與傳統邏輯斯迴歸差距甚遠。因而歸結出在模型比較上，應該要先避免邏輯斯迴歸低度配適的問題，再行比較，才較為公平。
In the prediction of binary variables, logistic regression is often selected asbase line for comparing. In many competitions, the prediction performancesof logistic regression are often unsatisfactory. Therefore, this study will discuss the comparison between logistic regression and random forest. In this study, we design a simulation to compare traditional logistic regression, additive Bspline logistic regression, tensor product B-spline logistic regression and random forest. The results showed that the latter three models only have a slightly different performance, which is far from the traditional logistic regression. Hence, if we want the comparison to be more fair, we need to deal with the problem of underfitting of logistic regression first. |
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Leathwick, J., Elith, J., and Hastie, T. (2006). Comparative performance of generalized additive models and multivariate adaptive regression splines for statistical modelling of species distributions. Ecological Modelling, 199(2):188 – 196. Predicting Species Distributions.
Li, M., Zhang, C., Xu, B., Xue, Y., and Ren, Y. (2020). A comparison of gam and gwr in modelling spatial distribution of japanese mantis shrimp (oratosquilla oratoria) in coastal waters. Estuarine, Coastal and Shelf Science, 244:106928.
Wood, S. N. and Augustin, N. H. (2002). Gams with integrated model selection using penalized regression splines and applications to environmental modelling. Ecological Modelling, 157(2):157 – 177. |
| Description: | 碩士
國立政治大學
統計學系
107354001 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0107354001 |
| Data Type: | thesis |
| DOI: | 10.6814/NCCU202100027 |
| Appears in Collections: | [統計學系] 學位論文
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