Answers are grounded in this paper and cite their sources.
Random trial demonstrates reduced decision trees maintain accuracy in binary predictions, indicating efficiency gains.
In this paper, we focus on the prediction phase of a random forest and study the problem of representing a bag of decision trees using a smaller bag of decision trees, where we only consider binary decision problems on the binary domain and simple decision trees in which an internal node is limited to querying the Boolean value of a single variable. As a main result, we show that given a constant integer c the majority function of an odd number n of variables can be represented by a bag of $$n-2c$$ decision trees each of which has size polynomial in n. We also show that a general bag of n decision trees can be represented by another bag containing only $$n-2c$$ polynomial-size decision trees, provided a small classification error is allowed. A related result on the k-out-of-n functions is presented as well.
No takes yet. Share an insight, caveat, or question.
Akutsu et al. (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: