Knowledge acquisition for expert systems
Knowledge acquisition for expert systems
A model of decision-making with sequential information-acquisition (part 1)
Decision Support Systems
A model of decision-making with sequential information-acquisition (part 2)
Decision Support Systems
International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
Unanimity and compromise among probability forecasters
Management Science
Empirical Learning as a Function of Concept Character
Machine Learning
Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
Predicting bank failures: A neural network approach
Applied Artificial Intelligence
Using accuracy in scientific discovery
EWSL-91 Proceedings of the European working session on learning on Machine learning
Evaluation of learning systems: an artificial data-based approach
EWSL-91 Proceedings of the European working session on learning on Machine learning
Trading MIPS and memory for knowledge engineering
Communications of the ACM
A composite approach to inducing knowledge for expert systems design
Management Science
Four types of noise in data for PAC learning
Information Processing Letters
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Applying Machine Learning to Semiconductor Manufacturing
IEEE Expert: Intelligent Systems and Their Applications
Machine Learning
Machine Learning
Journal of Artificial Intelligence Research
Evolutionary programming techniques for constrained optimizationproblems
IEEE Transactions on Evolutionary Computation
Sequential Decision Models for Expert System Optimization
IEEE Transactions on Knowledge and Data Engineering
Induction over Strategic Agents
Information Systems Research
A big-neuron based expert system
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
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We study the presence of economic bias in the training data used to develop inductive expert systems. Such bias arises when an expert considers economic factors in decision making. We find that the presence of economic bias is particularly harmful when there is an economic misalignment between the expert and the user of the induced expert system. Such misalignment is referred to as differential bias. The most significant contribution of this study is a training data debiasing procedure that uses a genetic algorithm to reconstruct training data that is relatively free of economic bias. We conduct a series of simulation experiments that show: 1) the economic performance of accuracy and value seeking algorithms is statistically the same when the training data has economic bias, 2) both accuracy and value seeking algorithms suffer in the presence of differential bias, 3) the proposed debiasing procedure significantly combats differential bias, and 4) the debiasing procedure is quite robust with respect to estimation errors in its input parameters.