Most rule learning systems posit hard decision boundaries for continuous attributes and point estimates of rule accuracy, with no measures of variance, which may seem arbitrary to ...
Lemuel R. Waitman, Douglas H. Fisher, Paul H. King
Rule systems have failed to attract much interest in large data analysis problems because they tend to be too simplistic to be useful or consist of too many rules for human interpr...
When a whole knowledge base must be derived for a fuzzy rule-based system, learning methods usually address this task with two or more sequential stages by separately designing ea...
We demonstrate that transformation-based learning can be used to correct noisy speech recognition transcripts in the lecture domain with an average word error rate reduction of 12...
We present an actor-critic scheme for reinforcement learning in complex domains. The main contribution is to show that planning and I/O dynamics can be separated such that an intra...
Pedro Alejandro Ortega, Daniel Alexander Braun, Si...