Yuta Nakahara

Bayesian Decision Theory on Decision Trees: Uncertainty Evaluation and Interpretability

Deterministic decision trees have difficulty in evaluating uncertainty especially for small samples. To solve this problem, we interpret the decision trees as stochastic models and consider prediction problems in the framework of Bayesian decision theory. Our models have three kinds of parameters: a…