A novel information theory method for filter feature selection

In this paper, we propose a novel filter for feature selection. Such filter relies on the estimation of the mutual information between features and classes. We bypass the estimation of the probability density function with the aid of the entropic-graphs approximation of Rényi entropy, and the subsequent approximation of the Shannon one. The complexity of such bypassing process does not depend on the number of dimensions but on the number of patterns/samples, and thus the curse of dimensionality is circumvented. We show that it is then possible to outperform a greedy algorithm based on the maximal relevance and minimal redundancy criterion. We successfully test our method both in the contexts of image classification and microarray data classification.

Representation of 2D objects with a topology preserving network

Comunicación presentada en el 2nd International Workshop on Pattern Recognition in Information Systems, Alicante, April, 2002.

The minimal overlap rule: restrictions on mergers for creditors’ consensus

As it is known, there is no rule satisfying additivity in the complete domain of bankruptcy problems. This paper proposes a notion of partial additivity in this context, to be called μ-additivity. We find out that this property, together with two quite compelling axioms, equal treatment of equals and continuity, identify the minimal overlap rule, introduced by O’Neill (Math. Soc. Sci. 2:345–371, 1982).

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

Temporal Control of Leaf Complexity by miRNA-Regulated Licensing of Protein Complexes

The tremendous diversity of leaf shapes has caught the attention of naturalists for centuries. In addition to interspecific and intraspecific differences, leaf morphologies may differ in single plants according to age, a phenomenon known as heteroblasty. In Arabidopsis thaliana, the progression from the juvenile to the adult phase is characterized by increased leaf serration. A similar trend is seen in species with more complex leaves, such as the A. thaliana relative Cardamine hirsuta, in which the number of leaflets per leaf increases with age. Although the genetic changes that led to the overall simpler leaf architecture in A. thaliana are increasingly well understood, less is known about the events underlying age-dependent changes within single plants, in either A. thaliana or C. hirsuta. Here, we describe a conserved miRNA transcription factor regulon responsible for an age-dependent increase in leaf complexity. In early leaves, miR319-targeted TCP transcription factors interfere with the function of miR164-dependent and miR164-independent CUC proteins, preventing the formation of serrations in A. thaliana and of leaflets in C. hirsuta. As plants age, accumulation of miR156-regulated SPLs acts as a timing cue that destabilizes TCP-CUC interactions. The destabilization licenses activation of CUC protein complexes and thereby the gradual increase of leaf complexity in the newly formed organs. These findings point to posttranslational interaction between unrelated miRNA-targeted transcription factors as a core feature of these regulatory circuits.

Tropical climate and vegetation simulations during the Heinrich event 1 using an Earth System Model of Intermediate Complexity (EMIC) - the University of Victoria Earth System-Climate Model (UVic ESCM)

Abrupt climate changes from 18 to 15 thousand years before present (kyr BP) associated with Heinrich Event 1 (HE1) had a strong impact on vegetation patterns not only at high latitudes of the Northern Hemisphere, but also in the tropical regions around the Atlantic Ocean. To gain a better understanding of the linkage between high and low latitudes, we used the University of Victoria (UVic) Earth System-Climate Model (ESCM) with dynamical vegetation and land surface components to simulate four scenarios of climate-vegetation interaction: the pre-industrial era, the Last Glacial Maximum (LGM), and a Heinrich-like event with two different climate backgrounds (interglacial and glacial). We calculated mega-biomes from the plant-functional types (PFTs) generated by the model to allow for a direct comparison between model results and palynological vegetation reconstructions. Our calculated mega-biomes for the pre-industrial period and the LGM corresponded well with biome reconstructions of the modern and LGM time slices, respectively, except that our pre-industrial simulation predicted the dominance of grassland in southern Europe and our LGM simulation resulted in more forest cover in tropical and sub-tropical South America. The HE1-like simulation with a glacial climate background produced sea-surface temperature patterns and enhanced inter-hemispheric thermal gradients in accordance with the "bipolar seesaw" hypothesis. We found that the cooling of the Northern Hemisphere caused a southward shift of those PFTs that are indicative of an increased desertification and a retreat of broadleaf forests in West Africa and northern South America. The mega-biomes from our HE1 simulation agreed well with paleovegetation data from tropical Africa and northern South America. Thus, according to our model-data comparison, the reconstructed vegetation changes for the tropical regions around the Atlantic Ocean were physically consistent with the remote effects of a Heinrich event under a glacial climate background.

The complexity of legal and ethical experience : studies in the method of normative subjects /

Includes bibliography.

Minimal luminance requirement for official highway signs. Final report.

Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, McLean, Va.

Adaptive linear classifier by linear programming,

Mode of access: Internet.

On the complexity of inferring join dependencies /

"UILU-ENG 79 1734."

On the complexity of edge labelings for trees /

"UILU-ENG 78 1740."

A study of concrete computational complexity /

"UIUCDCS-R-75-716"

Program manual for the programs ILLOD-MINSUM-CBS, ILLOD-MINSUM-CBSA, ILLOD-MINSUM-CBG, and ILLOD-MINSUM-CBGM, to derive minimal sums or irredundant disjunctive forms for switching functions /

"UILU-ENG 78 1719."

On a problem of Katona on minimal separating systems /

"This work was supported in part by the National Science Foundation under Grant No. US NSF GJ41538."