Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
386831 | Expert Systems with Applications | 2008 | 11 Pages |
Abstract
In recent years, many methods have been proposed to generate fuzzy rules from training instances for handling the Iris data classification problem. In this paper, we present a new method to generate fuzzy rules from training instances for dealing with the Iris data classification problem based on the attribute threshold value α, the classification threshold value β and the level threshold value γ, where α ∈ [0, 1], β ∈ [0, 1] and γ ∈ [0, 1]. The proposed method gets a higher average classification accuracy rate than the existing methods.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Shyi-Ming Chen, Fu-Ming Tsai,