This paper describes a genetic learning system called SIA, which learns attributes based rules from a set of preclassified examples. Examples may be described with a variable numbe...
This paper addresses the problem of classifying observations when features are context-sensitive, specifically when the testing set involves a context that is different from the t...
Research in systems where learning is integrated to other components like problem solving, vision, or natural language is becoming an important topic for Machine Learning. Situatio...
Enric Plaza, Agnar Aamodt, Ashwin Ram, Walter Van ...
In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...
It is empirically known that most incremental learning systems are order dependent, i.e. provide results that depend on the particular order of the data presentation. This paper ai...