Richard Jensen

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The level and apportionment of allozyme diversity were determined for 29 endemic (and 1 native) species from the Juan Fernández Islands, Chile. Mean diversities at the species level (H(es) = 0.065) are low but comparable to those measured for other insular endemics in the Pacific. A high mean proportion (0.338) of species-level diversity resides among(More)
We propose a new feature selection strategy based on rough sets and Particle Swarm Optimization (PSO). Rough sets has been used as a feature selection method with much success, but current hill-climbing rough set approaches to feature selection are inadequate at finding optimal reductions as no perfect heuristic can guarantee optimality. On the other hand,(More)
Semantics-preserving dimensionality reduction refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encountered in many areas such as machine learning, pattern recognition, and signal processing. This has found successful application in tasks that involve data sets containing huge numbers of features(More)
Due to the explosive growth of electronically stored information, automatic methods must be developed to aid users in maintaining and using this abundance of information e+ectively. In particular, the sheer volume of redundancy present must be dealt with, leaving only the information-rich data to be processed. This paper presents a novel approach, based on(More)
Feature selection (FS) refers to the problem of selecting those input attributes that are most predictive of a given outcome; a problem encountered in many areas such as machine learning, pattern recognition and signal processing. Unlike other dimensionality reduction methods, feature selectors preserve the original meaning of the features after reduction.(More)
There has been great interest in developing methodologies that are capable of dealing with imprecision and uncertainty. The large amount of research currently being carried out in fuzzy and rough sets is representative of this. Many deep relationships have been established, and recent studies have concluded as to the complementary nature of the two(More)
The membrane-proximal external region (MPER) of human immunodeficiency virus type 1 (HIV-1) gp41 bears the epitopes of two broadly neutralizing antibodies (Abs), 2F5 and 4E10, making it a target for vaccine design. A third Ab, Fab Z13, had previously been mapped to an epitope that overlaps those of 2F5 and 4E10 but only weakly neutralizes a limited set of(More)
Attribute selection (AS) refers to the problem of selecting those input attributes or features that are most predictive of a given outcome; a problem encountered in many areas such as machine learning, pattern recognition and signal processing. Unlike other dimensionality reduction methods, attribute selectors preserve the original meaning of the attributes(More)
One of the main obstacles facing current intelligent pattern recognition applications is that of dataset dimensionality. To enable these systems to be effective, a redundancy-removing step is usually carried out beforehand. Rough Set Theory (RST) has been used as such a dataset pre-processor with much success, however it is reliant upon a crisp dataset;(More)