專題演講 主講人：Prof. Wei-Yin Loh (University of Wisconsin, Madison)

  • 事件日期: 2026-05-29
  • AdminAdmin
  • 演講者:  /  主持人:
這是一張圖片


題　目：A Decision Tree Approach to Fitting Models to Missing Data

主講人：Prof. Wei-Yin Loh (University of Wisconsin, Madison)

時　間：115年5月29日(星期五)上午10:40-11:30
　　　　(上午10:20-10:40茶會於綜合一館428室舉行)

地　點：綜合一館427室

摘要

An old and still difficult question in statistics is how to fit regression models to data with missing values in the predictor variables. "Regression" is considered generally here, ranging from classical linear and logistic regression to modern machine learning methods. For more than fifty years, a standard practice has been imputation, which often requires assumptions that are often neither theoretically justifiable nor practically verifiable.  Missingness itself, however, can contain useful information that imputation destroys. We show how the GUIDE classification and regression tree algorithm can build prediction models without requiring imputation.  The GUIDE software and background material are available from https://pages.stat.wisc.edu/~loh/guide.html.