Decision-tree algorithms are known to be unstable: small variations in the training set can result in different trees and different predictions for the same validation examples. B...
Background: Structure-dependent substitution matrices increase the accuracy of sequence alignments when the 3D structure of one sequence is known, and are successful e.g. in fold ...
The alternating decision tree brings comprehensibility to the performance enhancing capabilities of boosting. A single interpretable tree is induced wherein knowledge is distribute...
Bernhard Pfahringer, Geoffrey Holmes, Richard Kirk...
This paper investigates an extension of classification trees to deal with uncertain information where uncertainty is encoded in possibility theory framework. Class labels in data s...
Ilyes Jenhani, Nahla Ben Amor, Salem Benferhat, Zi...
In this paper we tackle the main problem presented by the majority of Information Visualization techniques, that is, the limited number of data items that can be visualized simulta...