The Decision Tree Learning Algorithms (DTLAs) are getting keen attention from the natural language processing research comlnunity, and there have been a series of attempts to appl...
Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain comp...
We introduce a computationally feasible, "constructive" active learning method for binary classification. The learning algorithm is initially formulated for separable cl...
Iterative learning algorithms that approximate the solution of support vector machines (SVMs) have two potential advantages. First, they allow for online and active learning. Seco...
The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decisi...