The evolution of the influenza A virus to increase its host range is a major concern worldwide. Molecular mechanisms of increasing host range are largely unknown. Influenza surface proteins play determining roles in reorganization of host-sialic acid receptors and host range. In an attempt to uncover the physic-chemical attributes which govern HA subtyping, we performed a large scale functional...

When choosing between multiple alternatives, people usually do not have ready-made preferences in their mind but rather construct them on the go. The 2N-ary Choice Tree Model (Wollschlaeger & Diederich, 2012) proposes a preference construction process for N choice options from description, which is based on attribute weights, differences between attribute values, and noise. It is able to produc...

The structured representation of cases by attribute graphs in a Case-Based Reasoning (CBR) system for university course timetabling has been the subject of previous research by the authors. In that system, the case base is organised as a decision tree and the retrieval process chooses those cases that have similar (sub-)structures and attributes to the new case. The drawback of that approach is...

Attribute grammars are a powerful specification formalism for tree-based computation, particularly for software language processing. Various extensions have been proposed to abstract over common patterns in attribute grammar specifications. These include various forms of copy rules to support non-local dependencies, collection attributes, and expressing dependencies that are evaluated to a fixe...

In this paper, we propose an automatic leveling system for e-learning examination pool using the algorithm of the decision tree. The automatic leveling system is built to automatically level each question in the examination pool according its difficulty. Thus, an e-learning system can choose questions that are suitable for each learner according to individual background. Not all attributes are ...

This paper presents data mining techniques that can be used to study voting patterns in the United States House of Representatives and shows how the results can be interpreted. We processed the raw data available at http://clerk.house.gov, performed t-weight calculations, an attribute relevance study, association rule mining, and decision tree analysis and present and interpret interesting resu...

We herein describe a compiler generator, Rie, which is based on a one-pass-type attribute grammar. LR-attributed grammars are one class of attribute grammars in which attribute evaluation can be performed in one pass during LR parsing without creating a parse tree. Rie was developed based on a variant of an LR-attributed grammar called ECLR-attributed grammar (equivalence class LR-attributed gr...

We use a standard tree-structure representation for each individual. The GP constructs new attributes out of the continuous (real-valued) attributes of the data set being mined. Each individual corresponds to a candidate new attribute. The terminal set consists of all the continuous attributes in the data being mined. The function set consists of four arithmetic operators (+, -, *, /) and two r...

Trying to apply a visualization to data without prepro-cessing can often lead to incomprehensible results because of cluttered and confused displays. A solution is to use data mining to extract just the interesting results and to visualize them. There are two basic ways to carry out the mining: supervised and unsupervised. For the supervised case, the user has a particular goal in mind, while i...

Decision tree methods generally suppose that the number of categories of the attribute to be predicted is fixed. Breiman et al., with their Twoing criterion in CART, considered gathering the categories of the predicted attribute into two supermodalities. In this article, we propose an extension of this method. We try to merge the categories in an optimal unspecified number of supermodalities. O...