A memetic algorithm for evolutionary prototype selection: A scaling up approach

Prototype selection problem consists of reducing the size of databases by removing samples that are considered noisy or not influential on nearest neighbour classification tasks. Evolutionary algorithms have been used recently for prototype selection showing good results. However, due to the complexity of this problem when the size of the databases increases, the behaviour of evolutionary algorithms could deteriorate considerably because of a lack of convergence. This additional problem is known as the scaling up problem. Memetic algorithms are approaches for heuristic searches in optimization problems that combine a population-based algorithm with a local search. In this paper, we propose a model of memetic algorithm that incorporates an ad hoc local search specifically designed for optimizing the properties of prototype selection problem with the aim of tackling the scaling up problem. In order to check its performance, we have carried out an empirical study including a comparison between our proposal and previous evolutionary and non-evolutionary approaches studied in the literature. The results have been contrasted with the use of non-parametric statistical procedures and show that our approach outperforms previously studied methods, especially when the database scales up

AISIID: An artificial immune system for interesting information discovery on the web

There exist numerous systems for mining the web in search of relevant information but few exist for the discovery of interesting information. The discovery of interesting information is an advance on basic text mining in that it aims to identify text that is novel, unexpected or surprising to a user, whilst still being relevant. This article investigates the use of artificial immune systems (AIS) applied to discovery of interesting information. AIS are thought to confer the adaptability and learning required for this task. Artificial immune system for interesting information discovery (AISIID) is described in some detail, then an evaluative study is undertaken involving the subjective evaluation of the results by users. AISIID is found to discover pages rated more interesting by users than a comparative system

Genetic approach to constructive induction based on non-algebraic feature representation

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-45231-7_55Proceedings of 5th International Symposium on Intelligent Data Analysis, IDA 2003, Berlin, Germany, August 28-30, 2003The aim of constructive induction (CI) is to transform the original data representation of hard concepts with complex interaction into one that outlines the relation among attributes. CI methods based on greedy search suffer from the local optima problem because of high variation in the search space of hard learning problems. To reduce the local optima problem, we propose a CI method based on genetic (evolutionary) algorithms. The method comprises two integrated genetic algorithms to construct functions over subsets of attributes in order to highlight regularities for the learner. Using non-algebraic representation for constructed functions assigns an equal degree of complexity to functions. This reduces the difficulty of constructing complex features. Experiments show that our method is comparable with and in some cases superior to existing CI methods.This work has been partially supported by the Spanish Interdepartmental Commission for Science and Technology (CICYT), under Grants numbers TIC98-0247-C02-02 and TIC2002-1948

Machine learning by multi-feature extraction using genetic algorithms

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-30498-2_25Proceedings of 9th Ibero-American Conference on AI, Puebla, Mexico, November 22-26, 2004.Constructive Induction methods aim to solve the problem of learning hard concepts despite complex interaction in data. We propose a new Constructive Induction method based on Genetic Algorithms with a non-algebraic representation of features. The advantage of our method to some other similar methods is that it constructs and evaluates a combination of features. Evaluating constructed features together, instead of considering them one by one, is essential when number of interacting attributes is high and there are more than one interaction in concept. Our experiments show the effectiveness of this method to learn such concepts.This work has been partially supported by the Spanish Interdepartmental Commission for Science and Technology (CICYT), under Grant number TIC2002-194

Quality management systems as a link between management and employees

This paper analyses interactions between two parties (management and employees) with regard to the question of how to successfully manage and implement a quality management system (QMS). It also introduces practical possibilities for improving the employees\u27 understanding of why a QMS must be applied and how management should behave to make it possible. The paper also introduces a role of a third party (a quality representative) who must carefully choose his actions and must, above all else, be aware of the importance of open communication channels among the first two parties. Data were obtained from a research study using a survey among employees of a Slovenian information and communication technology company over a 2-year period. We found that communication between employees and management has significant importance on employee satisfaction. Therefore, communication is the essential element of successful and continuous improvement of the quality management system, in which management must be the first to show the awareness of the real purpose of the QMS, and must attract their employees\u27 attention as well as acknowledge their expectations. However, it should be noted that this factor can be stronger in a high technology company with a higher level of employee education. Conclusions are offered to improve the relationship among all parties through an improved status of the quality representative position over employees, his formal direct access to the management and the right to exercise and manage internal auditing of the system. Nevertheless, informally his role is far greater and consists once again of the crucial element of successfully and continuously improving of the QMS: communication