Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark
数百种机器学习分类器与离散选择模型的出行预测比较：实证基准
Numerous studies have compared machine learning (ML) and discrete choice models (DCMs) in predicting travel demand. However, these studies often lack generalizability as they compare models deterministically without considering contextual variations. To address this limitation, our study develops an empirical benchmark by designing a tournament model, thus efficiently summarizing a large number of experiments, quantifying the randomness in model comparisons, and using formal…