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Resources
BayesiaLab in action: presentations and case studies
Software presentations
- Bayesialab's introductory presentation Discover the world of the Bayesian networks with this first presentation of BayesiaLab.
- Analysis toolbox Bayesian networks are naturally legibles. BayesiaLab goes further with its very complete analysis toolbox.
- Bayesian network learning BayesiaLab is a powerful data mining tool that allows easily and simply discovering the knowledge hidden in your databases.
- Decision support Use of Decision and Utility nodes to discover the optimal action policies on a simple example: drilling of oil wells.
- Dynamic bayesian networks and action policy learning All the Bayesian networks used so far were static probabilistic models. BayesiaLab allows too representing dynamic models. By exploiting the power of Bayesian networks, it is possible to calculate your optimal action policies.
- Filtered/Censored States In a lot of studies, one need to use variables that are contingent on context, i.e. variables that only exist depending on the values of other variables (usage, configuration). We describe here how BayesiaLab takes rigorously these variables into account during learning and analysis
User guide
Case studies
Industry
- Modeling and simulation of dynamic systems Optimisation of the maintenance strategies of a complex industrial process, through a dynamic bayesian network.
- Production optimisation through feedback analysis Through this case study, discover the power of BayesiaLab’s automatic learning process in exploiting and benefitting from the data obtained from feedback.
Marketing
- Probabilistic structural equations and path analysis We describe in this presentation how BayesiaLab can be used to use Bayesian networks as a pragmatic alternative to Structural Equation Modeling, PLS and Path Analysis
- Studying consumer drivers Sensometrics meeting (St Catharine, Ontario, July 21st 2008) : studying consumer drivers with bayesian networks (in collaboration with Repères).
- Consumer segmentation Presentation at the SKIM conference (Barcelona, may 2008) of an innovative method for consumer segmentation through Bayesian networks (in collaboration with Repères).
- Customer characterization, development of profiles Customer profile learning from a database and characterization in order predict suitable products and detect fraud.
- Satisfaction questionnaire analysis BayesiaLab examines customer satisfaction with a fine tooth comb.
- Implementation of a Bayesian score Implementation of a Bayesian score and use of a graphic module to view the data.
Health
- Biocomputing transcriptome analysis Bioinformatics with BayesiaLab.
- Health trajectory analysis Prediction of medical needs with BayesiaLab.
Strategy
- Probabilistic structural equations and path analysis We describe in this presentation how BayesiaLab can be used to use Bayesian networks as a pragmatic alternative to Structural Equation Modeling, PLS and Path Analysis
- Political Analysis Analysis of the French Presidential Elections of April 2007.
Risk management
- Salmonella isolation Identification of factors associated with Salmonella isolation on pork carcasses via bayesian networks.
- Risk analysis and safety policy: example of transporting people Risk analysis for transporting people; modelling of a prevention policy.
- Cyber-crimes detection
Others
- Organization name identification Text-mining with BayesiaLab.



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