The new algorithm, named ID5R, lets one apply the ID3 induction process to learning tasks in which training instances are presented serially. Although the basic tree-building algorithms differ only in how the decision trees are constructed, experiments show that incremental training makes it possible...
Incremental Learning of Linear Model Trees 来自 国家科技图书文献中心 喜欢 0 阅读量: 56 作者:D Potts,C Sammut 摘要: A linear model tree is a decision tree with a linear functional model in each leaf. Previous model tree induction algorithms have been batch techniques that operate on the ...
By induction on the length of u this yields the statement of the lemma. □ Thus, whenever convenient, we assume in the sequel that a reader is in normal form. When designing readers, it is useful to be able to make some basic assumptions about the order of the words in the input...
incremental induction [‚iŋ·krə′ment·əl in′dək·shən] (electromagnetism) The quantity lying between the highest and lowest value of a magnetic induction at a point in a polarized material, when subjected to a small cycle of magnetization. ...
Lo, “Multi-Layer Incremental Induction”, Proceedings of the 5-th Pacific Rim International Conference on Artificial Intelligence, Springer-Verlag, pp. 24–32, 1998. About this Chapter Title An Incremental Learning Algorithm for Inferring Logical Rules from Examples in the Framework of the Common...
Stable Decision Trees: Using Local Anarchy for Efficient Incremental Learning This work deals with stability in incremental induction of decision trees. Stability problems arise when an induction algorithm must revise a decision tree... D Kalles,A Papagelis - 《International Journal on Artificial Intell...
This paper proposes the notion of 'topological relevance' as a means to formalize the complexity of a decision tree representation of a set of instances. It then presents an incremental algorithm, called IDL, for the induction of decision trees which are optimal according to this notion. IDL ...
Decision treesincremental inductionstabilityThis work deals with stability in incremental induction of decision trees. Stability problems arise when an induction algorithm must revise a decision tree very often and oscillations between similar concepts decrease learning speed. We introduce a heuristic and an...
learning (artificial intelligence)/ decision treeslocal anarchyincremental learningstabilityincremental inductionheuristic/ C6170K Knowledge engineering techniques C1230L Learning in AIThis work deals with stability in incremental induction of decision trees. Stability problems arise when an induction algorithm ...
original RRL. We introduce a fully incremental first order decision tree learning algorithm TG and integrate this algorithm in the RRL system to form RRL-TG. We demonstrate the performance gain on similar experiments to those that were used to demonstrate the behaviour of the original RRL system....