Title :
Adaptive features of machine learning methods
Author_Institution :
Lab. for Intelligent Syst., Univ. of Econ., Prague, Czech Republic
Abstract :
This paper gives a survey of (symbolic) machine learning methods, that exhibit significant features of adaptivity. The paper discusses incremental learning, learning in dynamically changing domains, knowledge integration, theory revision, case based reasoning and inductive logic programming.
Keywords :
adaptive systems; belief maintenance; case-based reasoning; inductive logic programming; learning (artificial intelligence); adaptive features; case based reasoning; dynamically changing domains; incremental learning; inductive logic programming; knowledge integration; smart adaptive system; survey; symbolic machine learning methods; theory revision; Adaptive systems; Artificial intelligence; Data mining; Decision trees; Inference algorithms; Iterative algorithms; Learning systems; Logic programming; Machine learning; Stress;
Conference_Titel :
Intelligent Systems, 2002. Proceedings. 2002 First International IEEE Symposium
Print_ISBN :
0-7803-7134-8
DOI :
10.1109/IS.2002.1042571
