Wrapper feature selection methods are widely used to select relevant features. However, wrappers only use a single classifier. The downside to this approach is that each classifier will have its own biases and will therefore select very different features. In order to overcome the biases of individual classifiers, this study introduces a new data mining method called wrapper-based decision tree...

The feature selection allows to choose P features among M (P < M) and thus to reduce the representation space. This process gets more and more useful because of the databases size increases. Therefore we propose a method based on preferences aggregation. It is an hybrid method that lies filter and wrapper approaches.

The proliferation of online information sources has led to an increased use of wrappers for extracting data from Web sources. While most of the previous research has focused on quick and efficient generation of wrappers, the development of tools for wrapper maintenance has received less attention. This is an important research problem because Web sources often change in ways that prevent the wr...

Glia play crucial roles in ensheathing axons, a process that requires an intricate series of glia-neuron interactions. The membrane-anchored protein Wrapper is present in Drosophila midline glia and is required for ensheathment of commissural axons. By contrast, Neurexin IV is present on the membranes of neurons and commissural axons, and is highly concentrated at their interfaces with midline ...

Adequate selection of features may improve accuracy and efficiency of classifier methods. There are two main approaches for feature selection: wrapper methods, in which the features are selected using the classifier, and filter methods, in which the selection of features is independent of the classifier used. Although the wrapper approach may obtain better performances, it requires greater comp...

The feature selection allows to choose P features among M (P<M) and thus to reduce the representation space of data. This process is increasingly useful because of the databases size increase. Therefore we propose a method based on preferences aggregation. It is an hybrid method between filter and wrapper approaches.

This paper presents a novel method for extracting information from collections of Web pages across different sites. Our method uses a standard wrapper induction algorithm and exploits named entity information. We introduce the idea of post-processing the extraction results for resolving ambiguous facts and improve the overall extraction performance. Postprocessing involves the exploitation of t...

Web wrappers play an important role in extracting information from distributed web sources and subsequently in the integration of heterogeneous data. Changes in the layout of web sources typically break the wrapper, leading to erroneous extraction of infomation. Monitoring and repairing broken wrappers is an important hurdle for data integration, since it is an expensive and painful procedure. ...