Browsing by Author "Madden, Michael G."
Now showing items 21-33 of 33
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On the Classification Performance of TAN and General Bayesian Networks
Madden, Michael G. (2008)Over a decade ago, Friedman et al. introduced the Tree Augmented Naïve Bayes (TAN) classifier, with experiments indicating that it significantly outperformed Naïve Bayes (NB) in terms of classification ... -
On the Classification Performance of TAN and General Bayesian Networks
Madden, Michael G. (Elsevier, 2009)Over a decade ago, Friedman et al. introduced the Tree Augmented Naïve Bayes (TAN) classifier, with experiments indicating that it significantly outperformed Naïve Bayes (NB) in terms of classification accuracy, ... -
One-class classification: taxonomy of study and review of techniques
Khan, Shehroz S.; Madden, Michael G. (Cambridge University Press (CUP), 2014-01-24)One-class classification (OCC) algorithms aim to build classification models when the negative class is either absent, poorly sampled or not well defined. This unique situation constrains the learning of efficient classifiers ... -
One-Class Support Vector Machine Calibration Using Particle Swarm Optimisation
Liu, Yang; Madden, Michael G. (2007)Abstract. Population-based search methods such as evolutionary algorithms, shuffled complex algorithms, simulated annealing and ant colony search are increasingly used as automatic calibration methods ... -
Open social data crime analytics
Ihsan, Ullah,; Lane, Caoilfhionn; Drury, Brett; Mellotte, Marc; Madden, Michael G. (IJCAI 17 Melbourne, 2017-07-20)Crime is under-reported. Reporting crime requires the victim to complete a number of administrative obligations. These obligations, as well as the nature of the crime, may create an inertia that discourages the reporting ... -
Probabilistic Detection of Short Events, with Application to Critical Care Monitoring
Manley, Geoffrey; Cohen, Mitchell; Staudenmayer, Kristan; Morabito, Diane; Madden, Michael G.; Russell, Stuart; Aleks, Norm (2008)We describe an application of probabilistic modeling and inference technology to the problem of analyzing sensor data in the setting of an intensive care unit (ICU). In particular, we consider the arterial-line blood ... -
Probabilistic Modeling of Sensor Artifacts in Critical Care
Manley, Geoffrey; Staudenmayer, Kristan; Cohen, Mitchell; Madden, Michael G.; Morabito, Diane; Aleks, Norm; Russell, Stuart (2008)We describe an application of probabilistic modeling and inference technology to the problem of analyzing sensor data in the setting of an intensive care unit (ICU). In particular, we consider the arterial-line blood ... -
Qualitative and Quantitative Analysis of Chlorinated Solvents using Raman Spectroscopy and Machine Learning
Madden, Michael G.; Hennessey, Kenneth; Leger, Marc N.; Ryder, Alan G.; Conroy, Jennifer (2005)The unambiguous identification and quantification of hazardous materials is of increasing importance in many sectors such as waste disposal, pharmaceutical manufacturing, and environmental protection. One particular ... -
Revealing the Origin and Nature of Drug Resistance of Dynamic Tumour Systems
Santiago-Mozos, Ricardo; Khan, Imtiaz A.; Madden, Michael G. (2010)In this paper, the authors identify the strategies that resistant subpopulations of cancer cells undertake to overcome the effect of the anticancer drug Topotecan. For the analyses of cell lineage data encoded from timelapse ... -
A survey of recent trends in one class classification
Khan, Shehroz S.; Madden, Michael G. (Springer Verlag - LNAI, 2009-08)The One Class Classification (OCC) problem is di fferent from the conventional binary/multi-class classi fication problem in the sense that in OCC, the negative class is either not present or not properly sampled. The ... -
The effect of principal component analysis on machine learning accuracy with high-dimensional spectral data
Howley, Tom; Madden, Michael G.; O’Connell, Marie-Louise; Ryder, Alan G. (Elsevier BV, 2006-09-01) -
The genetic kernel support vector machine: description and evaluation
Howley, Tom; Madden, Michael G. (Springer Nature, 2005-11-01)The Support Vector Machine (SVM) has emerged in recent years as a popular approach to the classification of data. One problem that faces the user of an SVM is how to choose a kernel and the specific parameters for that ... -
Towards inherently adaptive first person shooter agents using reinforcement learning
Glavin, Frank G. (2015-09-30)Reinforcement learning (RL) is a paradigm which involves an agent interacting with an environment. The agent carries out actions in the environment and receives positive reinforcement for actions that are deemed “good” and ...