This paper presents a hybrid filter–wrapper feature subset selection algorithm based on particle swarm optimization (PSO) for support vector machine (SVM) classification. The filter model is based on the mutual information and is a composite measure of feature relevance and redundancy with respect to the feature subset selected. The wrapper model is a modified discrete PSO algorithm. This hybri...

The performance of most practical classifiers improves when correlated or irrelevant features are removed. Machine based classification is thus often preceded by subset selection––a procedure which identifies relevant features of a high dimensional data set. At present, the most widely used subset selection technique is the so-called ‘‘wrapper’’ approach in which a search algorithm is used to i...

SYNONYMS web data extraction toolkit, web information extraction system, wrapper generator, wrapper generator toolkit, web macros, web scraper. DEFINITION A web data extraction system is a software system that automatically and repeatedly extracts data from web pages with changing content and delivers the extracted data to a database or some other application. The task of web data extraction pe...

Die Entwicklung komponentenstrukturierter E-Commerce-Software ist kostengünstig und schnell, da man die Systeme recht einfach aus wiederverwendbaren Softwarekomponenten zusammensetzt. Allerdings führt diese Entwurfsmethode zu einer neuen Art an Problemen für die Datensicherheit dieser Systeme. Insbesondere besteht die Gefahr, dass eine bösartige Komponente die gesamte Anwendung, in die sie eing...

The success of the Internet as a medium for the supply and commerce of various kinds of goods and services leads to a fast growing number of autonomous and heterogeneous providers that offer and sell goods and services electronically. The new market structures have already entered all kinds of markets. Approaches for market infrastructures usually try to cope with the heterogeneity of the provi...

This paper presents a novel feature selection approach to deal with issues of high dimensionality in biomedical data classification. Extensive research has been performed in the field of pattern recognition and machine learning. Dozens of feature selection methods have been developed in the literature, which can be classified into three main categories: filter, wrapper and hybrid approaches. Fi...

Many machine learning applications require classi ers that minimize an asymmetric loss function rather than the raw misclassi cation rate. We study methods for modifying C4.5 to incorporate arbitrary loss matrices. One way to incorporate loss information into C4.5 is to manipulate the weights assigned to the examples from di erent classes. For 2-class problems, this works for any loss matrix, b...

This paper presents SoftMealy, a novel Web wrapper representation formalism. This representation is based on a finite-state transducer (FST) and contextual rules, which allow a wrapper to wrap semistructured Web pages containing missing attributes, multiple attribute values, variant attribute permutations, exceptions and typos, the features that no previous work can handle. A SoftMealy wrapper ...

In the present work, a graphical user interface is developed to automate in-core fuel management using MCODE, an MCNP-ORIGEN linkage code. Data abstraction is achieved by means of five object classes that define the run, fuel assembly locations, fuel assemblies, fuel paths, and materials. The GUI and an associated fuel management wrapper were developed in Python, with the PyQt extension being u...

One of the vexing problems that besets concurrent use of multiple, heterogeneous resources is format multiplicity. C(2)M aims to equip scientists with a wrapper generator on their desktop. The wrapper generator can build wrappers, or converters that can convert data from or into different formats, from a high-level description of the formats. The language in which such a high-level description ...