Browsing by Author "Madden, Michael G."
Now showing items 1-20 of 33
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Accurate Bayesian prediction of cardiovascular-related mortality using ambulatory blood pressure measurements
O'Neill, James; Madden, Michael G.; Dolan, Eamon (Springer Cham, 2017-05-30)Hypertension is the leading cause of cardiovascular-related mortality (CVRM), affecting approximately 1 billion people worldwide. To enable patients at significant risk of CVRM to be treated appropriately, it is essential ... -
Adaptive shooting for bots in first person shooter games using reinforcement learning
Glavin, Frank G.; Madden, Michael G. (Institute of Electrical and Electronics Engineers (IEEE), 2015-06-01)In current state-of-the-art commercial first person shooter games, computer controlled bots, also known as nonplayer characters, can often be easily distinguishable from those controlled by humans. Tell-tale signs such as ... -
An improved genetic programming technique for the classification of raman spectra
Hennessy, Kenneth; Madden, Michael G.; Conroy, Jennifer; Ryder, Alan G. (Elsevier BV, 2005-08-01) -
Analysis of the Effects of Unexpected Outliers in the Classification of Spectroscopy Data
Glavin, Frank G.; Madden, Michael G. (2009)Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, because they assume all classes are characterised by the data, whereas in many ... -
Arrhythmia Identification from ECG Signals with a Neural Network Classifier Based on a Bayesian Framework
Lyons, Gerard J.; Chambers, Des; Schukat, Michael; Madden, Michael G.; Gao, Dayong (2004)This paper presents an ANN-based diagnostic system for arrhythmia using Neural Network Classifier with Bayesian framework by time series biosignals. The Neural Network Classifier is built by the use of logistic regression ... -
Bayesian ANN Classifier for ECG Arrhythmia Diagnostic System: A Comparison Study
Lyons, Gerard J.; Chambers, Des; Madden, Michael G.; Gao, Dayong (2005)Abstract¿This paper outlines a system for detection of cardiac arrhythmias within ECG signals, based on a Bayesian Artificial Neural Network (ANN) classifier. The Bayesian (or Probabilistic) ANN Classifier is built by the ... -
Bayesian networks for mathematical models: techniques for automatic construction and efficient inference
Enright, Catherine G.; Madden, Michael G.; Madden, Niall (Elsevier BV, 2013-02-01) -
Classification of a Target Analyte in Solid Mixtures using Principal Component Analysis, Support Vector Machines and Raman Spectroscopy
Madden, Michael G.; Leger, Marc N.; Ryder, Alan G.; Howley, Tom; O Connell, Marie-Louise (2005)The quantitative analysis of illicit materials using Raman spectroscopy is of widespread interest for law enforcement and healthcare applications. One of the difficulties faced when analysing illicit mixtures is the ... -
A Data-Driven Exploration of Factors Affecting Student Performance in a Third-Level Institution
Madden, Michael G.; Lyons, William; Kavanagh, Ita (2008)This paper describes an application of data mining techniques to the analysis of student academic records, collected at Limerick Institute of Technology, with the goal of acquiring clearer, evidence-based ... -
The Effect of Principal Component Analysis on Machine Learning Accuracy with High Dimensional Spectral Data
Ryder, Alan G.; O Connell, Marie-Louise; Madden, Michael G.; Howley, Tom (2005)The classi¿cation of high dimensional data, such as images, gene-expression data and spectral data, poses an interesting challenge to machine learning, as the presence of high numbers of redundant or highly correlated ... -
The Evolution of a Kernel-Based Distance Metric for k-NN Regression
Madden, Michael G.; Howley, Tom (2007)k-Nearest Neighbours (k-NN) is a well understood and widely-used approach to classification and regression problems. In many cases, such applications of k-NN employ the standard Euclidean distance metric for the determination ... -
An evolutionary approach to automatic kernel construction
Madden, Michael G.; Howley, Tom (2006)Abstract. Kernel-based learning presents a unified approach to machine learning problems such as classification and regression. The selection of a kernel and associated parameters is a critical step in the application of ... -
The Genetic Evolution of Kernels for Support Vector Machine Classifiers
Madden, Michael G.; Howley, Tom (2004)Abstract. The Support Vector Machine (SVM) has emerged in recent years as a popular approach to the classi¿cation of data. One problem that faces the user of an SVM is how to choose a kernel and the speci¿c parameters for ... -
Improving spectral library search by redefining similarity measures
Garg, Ankita; Enright, Catherine G.; Madden, Michael G. (Journal Of Chemical Information And Modeling, 2015-04-22)Similarity plays a central role in spectral library search. The goal of spectral library search is to identify those spectra in a reference library of known materials that most closely match an unknown query spectrum, on ... -
A Machine Learning Application for Classification of Chemical Spectra
Madden, Michael G.; Howley, Tom (2008)This paper presents a software package that allows chemists to analyze spectroscopy data using innovative machine learning (ML) techniques. The package, designed for use in conjunction with lab-based spectroscopic ... -
Machine learning methods for quantitative analysis of Raman spectroscopy data
Madden, Michael G.; Ryder, Alan G. (Society of Photo-optical Instrumentation Engineers (SPIE), 2003-08-27)The automated identification and quantification of illicit materials using Raman spectroscopy is of significant importance for law enforcement agencies. This paper explores the use of Machine Learning (ML) methods in ... -
Multi-Class and Single-Class Classification Approaches to Vehicle Model Recognition from Images
Madden, Michael G.; Munroe, Daniel T. (2005)This paper investigates the use of machine learning classification techniques applied to the task of recognising the make and model of vehicles. Although a number of vehicle classification systems already exist, most of ... -
Neural Network Approach to Predicting Stock Exchange Movements using External Factors
Madden, Michael G.; O'Connor, Niall (2005)The aim of this study is to evaluate the effectiveness of using external indicators, such as commodity prices and currency exchange rates, in predicting movements in the Dow Jones Industrial Average index. The performance ... -
NUI Galway - UL Alliance Engineering, Informatics and Science Research Day 2013 - Book of Abstracts
Madden, Michael G.; Ó Brádaigh, Conchúr M. (NUI Galway, 2013)This is the book of research abstracts from the NUI Galway - University of Limerick Third Annual Engineering, Informatics and Science Research Day, held in the National University of Ireland, Galway, on 11 April 2013. This ... -
NUI Galway - UL Alliance First Annual Engineering and Informatics Research Day - Book of Abstracts
Madden, Michael G.; Corcoran, Peter; Keane, Marcus; McGrath, Sean (2011-04-07)