We investigate an inherent limitation of top-down decision tree induction in which the continuous partitioning of the instance space progressively lessens the statistical support o...
Computer problem diagnosis remains a serious challenge to users and support professionals. Traditional troubleshooting methods relying heavily on human intervention make the proce...
Chun Yuan, Ni Lao, Ji-Rong Wen, Jiwei Li, Zheng Zh...
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
The selection of the action to do next is one of the central problems faced by autonomous agents. In AI, three approaches have been used to address this problem: the programming-b...
We study multiple predicate learning in an empirical setting. Problems with existing inductive logic programming approaches in this setting are sketched and an empirical ILP syste...