DIVACE: Diverse and Accurate Ensemble Learning Algorithm

  title={DIVACE: Diverse and Accurate Ensemble Learning Algorithm},
  author={Arjun Chandra and Xin Yao},
In order for a neural network ensemble to generalise properly, two factors are considered vital. One is the diversity and the other is the accuracy of the networks that comprise the ensemble. There exists a tradeoff as to what should be the optimal measures of diversity and accuracy. The aim of this paper is to address this issue. We propose the DIVACE algorithm which tries to produce an ensemble as it searches for the optimum point on the diversity-accuracy curve. The DIVACE algorithm… CONTINUE READING
Highly Cited
This paper has 124 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 54 extracted citations

Pareto-Based Multiobjective Machine Learning: An Overview and Case Studies

IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) • 2008
View 9 Excerpts
Highly Influenced

124 Citations

Citations per Year
Semantic Scholar estimates that this publication has 124 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.

Similar Papers

Loading similar papers…