Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
Machine Learning - Special issue on learning with probabilistic representations
A tutorial on learning with Bayesian networks
Learning in graphical models
Probabilistic Networks and Expert Systems
Probabilistic Networks and Expert Systems
Learning Bayesian networks from data: an information-theory based approach
Artificial Intelligence
Bayesian Networks for Data Mining
Data Mining and Knowledge Discovery
Distributed Data Mining in Credit Card Fraud Detection
IEEE Intelligent Systems
Induction of Recursive Bayesian Classifiers
ECML '93 Proceedings of the European Conference on Machine Learning
Adjusted Probability Naive Bayesian Induction
AI '98 Selected papers from the 11th Australian Joint Conference on Artificial Intelligence on Advanced Topics in Artificial Intelligence
Learning Bayesian Network Classifiers for Credit Scoring Using Markov Chain Monte Carlo Search
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Bayesian Models for Early Warning of Bank Failures
Management Science
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Appraisal of companies is an important business activity. We mainly apply Bayesian networks for this classification task for Japanese electric company data. Firstly, few standard statistical techniques are performed. Then Bayesian networks are applied in four steps: (1) for implementing a current procedure of economical experts, where economical variables are clustered and then summarised for computing a score for deciding the economical state of the company, (2) the same is done but with clustering of economical variables based on data, (3) the naive Bayes classifier and (4) an improved naive Bayes classifier through adjusting its conditional density of each feature variable given the class variable, which are initially obtained by maximum likelihood estimation. Adjustments are done by using the simulated annealing optimisation. Finally, a sensible way for appraisal of companies is discussed.