Sciweavers

Share
AAAI
1996

Generation of Attributes for Learning Algorithms

8 years 3 months ago
Generation of Attributes for Learning Algorithms
Inductive algorithms rely strongly on their representational biases, Constructive induction can mitigate representational inadequacies. This paper introduces the notion of a relative gain measure and describes a new constructive induction algorithm (GALA) which is independent of the learning algorithm. Unlike most previous research on constructive induction, our methods are designed as preprocessing step before standard machine learning algorithms are applied. We present the results which demonstrate the effectiveness of GALA on artificial and real domains for several learners: C4.5, CN2, perceptron and backpropagation.
Yuh-Jyh Hu, Dennis F. Kibler
Added 02 Nov 2010
Updated 02 Nov 2010
Type Conference
Year 1996
Where AAAI
Authors Yuh-Jyh Hu, Dennis F. Kibler
Comments (0)
books