Search results for "computability"
showing 7 items of 27 documents
Ultimate Order Statistics-Based Prototype Reduction Schemes
2013
Published version of a chapter in the book: AI 2013: Advances in Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-319-03680-9_42 The objective of Prototype Reduction Schemes (PRSs) and Border Identification (BI) algorithms is to reduce the number of training vectors, while simultaneously attempting to guarantee that the classifier built on the reduced design set performs as well, or nearly as well, as the classifier built on the original design set. In this paper, we shall push the limit on the field of PRSs to see if we can obtain a classification accuracy comparable to the optimal, by condensing the information in the data set into a single tr…
Peptide classification using optimal and information theoretic syntactic modeling
2010
Accepted version of an article published in the journal: Pattern Recognition. Published version available on Sciverse: http://dx.doi.org/10.1016/j.patcog.2010.05.022 We consider the problem of classifying peptides using the information residing in their syntactic representations. This problem, which has been studied for more than a decade, has typically been investigated using distance-based metrics that involve the edit operations required in the peptide comparisons. In this paper, we shall demonstrate that the Optimal and Information Theoretic (OIT) model of Oommen and Kashyap [22] applicable for syntactic pattern recognition can be used to tackle peptide classification problem. We advoca…
Imposing tree-based topologies onto self organizing maps
2011
Accepted version of an article from the journal Information Sciences. Definitive published version available on Elsevier Science Direct: http://dx.doi.org/10.1016/j.ins.2011.04.038 The beauty of the Kohonen map is that it has the property of organizing the codebook vectors, which represent the data points, both with respect to the underlying distribution and topologically. This topology is traditionally linear, even though the underlying lattice could be a grid, and this has been used in a variety of applications [23,35,40]. The most prominent efforts to render the topology to be structured involves the Evolving Tree (ET) due to Pakkanen et al. [36], and the Self-Organizing Tree Maps (SOTM)…
Generalized Bayesian pursuit: A novel scheme for multi-armed Bernoulli bandit problems
2011
Published version of a chapter in the book: IFIP Advances in Information and Communication Technology. Also available from the publisher at: http;//dx.doi.org/10.1007/978-3-642-23960-1_16 In the last decades, a myriad of approaches to the multi-armed bandit problem have appeared in several different fields. The current top performing algorithms from the field of Learning Automata reside in the Pursuit family, while UCB-Tuned and the ε -greedy class of algorithms can be seen as state-of-the-art regret minimizing algorithms. Recently, however, the Bayesian Learning Automaton (BLA) outperformed all of these, and other schemes, in a wide range of experiments. Although seemingly incompatible, in…
Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes
2010
Accepted version of an article published in the journal: Pattern Recognition. Published version on Sciverse: http://dx.doi.org/10.1016/j.patcog.2010.01.018 Linear dimensionality reduction (LDR) techniques have been increasingly important in pattern recognition (PR) due to the fact that they permit a relatively simple mapping of the problem onto a lower-dimensional subspace, leading to simple and computationally efficient classification strategies. Although the field has been well developed for the two-class problem, the corresponding issues encountered when dealing with multiple classes are far from trivial. In this paper, we argue that, as opposed to the traditional LDR multi-class schemes…
On Optimizing Locally Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes
2010
Published version of an article from the Book: AI 2010: Advances in Artificial Intelligence, Spinger. Also available on Springerlink: http://dx.doi.org/10.1007/978-3-642-17432-2_16 This paper concerns the use of Prototype Reduction Schemes (PRS) to optimize the computations involved in typical k-Nearest Neighbor (k-NN) rules. These rules have been successfully used for decades in statistical Pattern Recognition (PR) applications, and have numerous applications because of their known error bounds. For a given data point of unknown identity, the k-NN possesses the phenomenon that it combines the information about the samples from a priori target classes (values) of selected neighbors to, for …
A two-armed bandit collective for examplar based mining of frequent itemsets with applications to intrusion detection
2011
Chapter from the book: Computational Collective Intelligence. Technologies and Applications. Also available from the publisher at SpringerLink: http://dx.doi.org/10.1007/978-3-642-23935-9_7 Over the last decades, frequent itemset mining has become a major area of research, with applications including indexing and similarity search, as well as mining of data streams, web, and software bugs. Although several efficient techniques for generating frequent itemsets with a minimum support (frequency) have been proposed, the number of itemsets produced is in many cases too large for effective usage in real-life applications. Indeed, the problem of deriving frequent itemsets that are both compact an…