Now showing items 1-20 of 66

  • Assessment and optimisation of STCA performance: Using the Pareto optimal receiver operating characteristic 

    Reckhouse, William; Everson, Richard M.; Fieldsend, Jonathan E.; Bush, David; Arnold, Trevor; Hayward, Richard; Slater, Keith (2008)
    Short Term Conflict Alert (STCA) systems are complex software programs, with many parameters that must be adjusted to achieve best performance. We describe a simple evolutionary algorithm for optimising the trade-off between ...
  • The Bayesian Decision Tree Technique with a Sweeping Strategy 

    Schetinin, Vitaly; Fieldsend, Jonathan E.; Partridge, Derek; Krzanowski, Wojtek J.; Everson, Richard M.; Bailey, Trevor C.; Hernandez, Adolfo (2004)
    The uncertainty of classification outcomes is of crucial importance for many safety critical applications including, for example, medical diagnostics. In such applications the uncertainty of classification can be reliably ...
  • A Bayesian Framework for Active Learning 

    Fredlund, Richard; Everson, Richard M.; Fieldsend, Jonathan E. (Institute of Electrical and Electronics Engineers (IEEE), 2010)
    We describe a Bayesian framework for active learning for non-separable data, which incorporates a query density to explicitly model how new data is to be sampled. The model makes no assumption of independence between queried ...
  • Bayesian inductively learned modules for safety critical systems 

    Fieldsend, Jonathan E.; Bailey, Trevor C.; Everson, Richard M.; Krzanowski, Wojtek J.; Partridge, Derek; Schetinin, Vitaly (Interface Foundation of North America, Inc., 2003)
    This work examines the use of Bayesian inductively learned software modules for safety critical systems. Central to the safety critical application is the desire to generate confidence measures associated with predictions. ...
  • A Bayesian Methodology for Estimating Uncertainty of Decisions in Safety-Critical Systems 

    Schetinin, Vitaly; Fieldsend, Jonathan E.; Partridge, Derek; Krzanowski, Wojtek J.; Bailey, Trevor C.; Everson, Richard M.; Hernandez, Adolfo (IOS Press, 2006)
  • Cardinality constrained portfolio optimisation 

    Fieldsend, Jonathan E.; Matatko, John; Peng, Ming (Springer Berlin Heidelberg, 2004)
    The traditional quadratic programming approach to portfolio optimisation is difficult to implement when there are cardinality constraints. Recent approaches to resolving this have used heuristic algorithms to search for ...
  • Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique 

    Schetinin, Vitaly; Fieldsend, Jonathan E.; Partridge, Derek; Krzanowski, Wojtek J.; Everson, Richard M.; Bailey, Trevor C.; Hernandez, Adolfo (Springer, 2006)
    Multiple Classifier Systems (MCSs) allow evaluation of the uncertainty of classification outcomes that is of crucial importance for safety critical applications. The uncertainty of classification is determined by a trade-off ...
  • Computing with confidence: a Bayesian approach 

    Partridge, Derek; Fieldsend, Jonathan E.; Krzanowski, Wojtek J.; Bailey, Trevor C.; Everson, Richard M.; Schetinin, Vitaly (2006)
    Bayes’ rule is introduced as a coherent strategy for multiple recomputations of classifier system output, and thus as a basis for assessing the uncertainty associated with a particular system results --- i.e. a basis for ...
  • Confidence in Classification: A Bayesian Approach 

    Krzanowski, Wojtek J.; Bailey, Trevor C.; Partridge, Derek; Fieldsend, Jonathan E.; Everson, Richard M.; Schetinin, Vitaly (Springer Verlag, 2006)
    Bayesian classification is currently of considerable interest. It provides a strategy for eliminating the uncertainty associated with a particular choice of classifiermodel parameters, and is the optimal decision-theoretic ...
  • Confident interpretation of Bayesian decision tree ensembles for clinical applications 

    Schetinin, Vitaly; Fieldsend, Jonathan E.; Partridge, Derek; Coats, Timothy J.; Krzanowski, Wojtek J.; Everson, Richard M.; Bailey, Trevor C.; Hernandez, Adolfo (Institute of Electrical and Electronics Engineers (IEEE), 2007)
    Bayesian averaging (BA) over ensembles of decision models allows evaluation of the uncertainty of decisions that is of crucial importance for safety-critical applications such as medical diagnostics. The interpretability ...
  • Dominance Measures for Multi-Objective Simulated Annealing 

    Smith, Kevin I.; Everson, Richard M.; Fieldsend, Jonathan E. (Institute of Electrical and Electronics Engineers (IEEE), 2004)
    Simulated annealing (SA) is a provably convergent optimiser for single-objective (SO) problems. Previously proposed MO extensions have mostly taken the form of an SO SA optimising a composite function of the objectives. ...
  • Dominance-Based Multiobjective Simulated Annealing 

    Smith, Kevin I.; Everson, Richard M.; Fieldsend, Jonathan E.; Murphy, Chris; Misra, Rashmi (Institute of Electrical and Electronics Engineers (IEEE), 2008)
    Simulated annealing is a provably convergent optimizer for single-objective problems. Previously proposed multiobjective extensions have mostly taken the form of a single-objective simulated annealer optimizing a composite ...
  • Edges of Mutually Non-dominating Sets 

    Everson, Richard M.; Walker, David J.; Fieldsend, Jonathan E. (ACM, 2013-07)
    Multi-objective optimisation yields an estimated Pareto front of mutually non-dominating solutions, but with more than three objectives understanding the relationships between solutions is challenging. Natural solutions ...
  • Efficiently identifying pareto solutions when objective values change 

    Fieldsend, Jonathan E.; Everson, Richard M. (ACM, 2014)
    In many multi-objective problems the objective values assigned to a particular design can change during the course of an optimisation. This may be due to dynamic changes in the problem itself, or updates to estimated ...
  • Elite Accumulative Sampling Strategies for Noisy Multi-Objective Optimisation 

    Fieldsend, Jonathan E. (Springer, 2015)
    When designing evolutionary algorithms one of the key concerns is the balance between expending function evaluations on exploration versus exploitation. When the optimisation problem experiences observational noise, there ...
  • Estimating Classification Uncertainty of Bayesian Decision Tree Technique on Financial Data 

    Schetinin, Vitaly; Fieldsend, Jonathan E.; Partridge, Derek; Krzanowski, Wojtek J.; Everson, Richard M.; Bailey, Trevor C.; Hernandez, Adolfo (Springer Berlin Heidelberg, 2007)
    Summary Bayesian averaging over classification models allows the uncertainty of classification outcomes to be evaluated, which is of crucial importance for making reliable decisions in applications such as financial in ...
  • Experimental Comparison of Classification Uncertainty for Randomised and Bayesian Decision Tree Ensembles 

    Schetinin, Vitaly; Partridge, Derek; Krzanowski, Wojtek J.; Everson, Richard M.; Fieldsend, Jonathan E.; Bailey, Trevor C.; Hernandez, Adolfo (Springer Berlin Heidelberg, 2004)
    In this paper we experimentally compare the classification uncertainty of the randomised Decision Tree (DT) ensemble technique and the Bayesian DT technique with a restarting strategy on a synthetic dataset as well as on ...
  • Financial Time Series Forecasts using Fuzzy and Long Memory Pattern Recognition Systems 

    Singh, Sameer; Fieldsend, Jonathan E. (Institute of Electrical and Electronics Engineers (IEEE), 2000)
    In this paper, the concept of long memory systems for forecasting is developed. The pattern modelling and recognition system and fuzzy single nearest neighbour methods are introduced as local approximation tools for ...
  • Formulation and comparison of multi-class ROC surfaces 

    Fieldsend, Jonathan E.; Everson, Richard M. (2005)
    The Receiver Operating Characteristic (ROC) has become a standard tool for the analysis and comparison of classifiers when the costs of misclassification are unknown. There has been relatively little work, however, examining ...
  • Full Elite Sets for Multi-Objective Optimisation 

    Everson, Richard M.; Fieldsend, Jonathan E.; Singh, Sameer (Springer, 2002)
    Multi-objective evolutionary algorithms frequently use an archive of non-dominated solutions to approximate the Pareto front. We show that the truncation of this archive to a limited number of solutions can lead to oscillating ...