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Article
Open AccessGenome classification by gene distribution: An overlap** subspace clustering approach
Genomes of lower organisms have been observed with a large amount of horizontal gene transfers, which cause difficulties in their evolutionary study. Bacteriophage genomes are a typical example. One recent app...
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Chapter and Conference Paper
Information Theoretic Classification of Problems for Metaheuristics
This paper proposes a model for metaheuristic research which recognises the need to match algorithms to problems. An empirical approach to producing a map** from problems to algorithms is presented. This map...
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Article
Polynomial kernel adaptation and extensions to the SVM classifier learning
Three extensions to the Kernel-AdaTron training algorithm for Support Vector Machine classifier learning are presented. These extensions allow the trained classifier to adhere more closely to the constraints i...
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Article
Open AccessGene function prediction based on genomic context clustering and discriminative learning: an application to bacteriophages
Existing methods for whole-genome comparisons require prior knowledge of related species and provide little automation in the function prediction process. Bacteriophage genomes are an example that cannot be ea...
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Chapter and Conference Paper
Combining News and Technical Indicators in Daily Stock Price Trends Prediction
Stock market prediction has always been one of the hottest topics in research, as well as a great challenge due to its complex and volatile nature. However, most of the existing methods neglect the impact from...
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Chapter and Conference Paper
Semi-supervised Learning of Dynamic Self-Organising Maps
We present a semi-supervised learning method for the Growing Self-Organising Maps (GSOM) that allows fast visualisation of data class structure on the 2D network. Instead of discarding data with missing values...
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Chapter and Conference Paper
Scalable Dynamic Self-Organising Maps for Mining Massive Textual Data
Traditional text clustering methods require enormous computing resources, which make them inappropriate for processing large scale data collections. In this paper we present a clustering method based on the wo...
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Article
Particle Swarm Optimisation for Protein Motif Discovery
In this paper, a modified particle swarm optimisation algorithm is proposed for protein sequence motif discovery. Protein sequences are represented as a chain of symbols and a protein sequence motif is a short...
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Chapter
Mining of Labeled Incomplete Data Using Fast Dimension Partitioning
Two Dimensional Partitioning Techniques are proposed in this paper for fast mining of labeled data with missing values. The first Dimensional Partitioning Technique (DPT1) generates a classifier model by the u...
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Chapter
Fast Perceptron Learning by Fuzzy Controlled Dynamic Adaptation of Network Parameters
Application of fuzzy control for obtaining better performance from conventional neural networks is a new area in the field of fuzzy-neural combined systems. Conventional backpropagation algorithm for example c...
