In this paper, we consider decision trees as a means of knowledge representation. To this end, we design three algorithms for decision tree construction that are based on extensions of dynamic programming. We study three parameters of the decision trees constructed by these algorithms: number of nodes, global misclassification rate, and local misclassification rate.
|Original language||English (US)|
|Title of host publication||28th International Workshop on Concurrency, Specification and Programming, CS and P 2019|
|State||Published - Jan 1 2019|