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%.

How Does Intimate Partner Violence Differ Depending on Level of Rurality of Residential Area in Spain?

Intimate partner violence (IPV) is recognized as a worldwide public health problem. Most theories ascribe IPV to individual, family, or cultural factors. Authors analyzed different residential areas in Spain in terms of IPV frequency as well as its impact on health and the use of services. A standardized self-administered cross-sectional survey was administered to ever-partnered adult women ages 18 to 70 years receiving care at primary health care centers (N = 10,322). Logistic regression analyzed the association between the level of rurality and health indicators, IPV, and use of services. The lowest frequency of IPV among women is reflected in higher rurality. Women of medium and low rurality presented a poorer self-perceived health and more physical health problems. Women from medium and low rurality areas declared seeking health services more frequently. These results show the importance of the environment in health and indicate the need for research on urban–rural differences in health problems to develop specific public health programs for each country.

Golf course irrigation and self-sufficiency water in Southern Spain

During the first decade of the 21st century, many golf courses were developed in the Southeast of Spain, which greatly increased the number of these facilities. Almost all of these golf courses have been accompanied by large residential developments composed of thousands of dwelling units. This article seeks to identify the factors that influence golf courses’ water consumption and estimate the number of dwelling units that an associated residential development needs to have to provide the effluent necessary to fully meet the irrigation needs of a golf course. The study indicates that private golf courses achieve greater levels of irrigation efficiency than public golf courses and that the golf courses associated with residential developments subject the irrigation needs of the grassland to the sale requirements of the real estate properties. The study also estimates that a golf course requires approximately 3000 dwelling units with an average annual occupancy of 33% to achieve self-sufficiency for irrigation.