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Bayesian ANN Classifier for ECG Arrhythmia Diagnostic System: A Comparison Study
(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 ...
Classification of a Target Analyte in Solid Mixtures using Principal Component Analysis, Support Vector Machines and Raman Spectroscopy
(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 ...
The Effect of Principal Component Analysis on Machine Learning Accuracy with High Dimensional Spectral Data
(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 ...
On the Classification Performance of TAN and General Bayesian Networks
(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 ...
Probabilistic Detection of Short Events, with Application to Critical Care Monitoring
(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 ...
A Data-Driven Exploration of Factors Affecting Student Performance in a Third-Level Institution
(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 Evolution of a Kernel-Based Distance Metric for k-NN Regression
(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 ...
Probabilistic Modeling of Sensor Artifacts in Critical Care
(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
(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 ...
The Genetic Evolution of Kernels for Support Vector Machine Classifiers
(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 ...