Resources
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Tutorials
- Introduction to Bayesian networks
- Bayesialab's introductory presentation
- Analysis toolbox
- Bayesian network learning
- Decision support
- Dynamic bayesian networks and action policy learning
- Filtered/Censored States
- Probabilistic structural equations
- BayesiaLab Knowledge Elicitation Environment
- Driver analysis and product optimization with BayesiaLab
- Modeling Vehicle Choice and Simulating Market Share
- Probabilistic Latent Factor Induction
- Paradoxes and Fallacies
- Unsupervised and Supervised Learning with BayesiaLab
- Causal Inference and Direct Effects
- Causal Inference and Direct Effects
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User Guide
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BayesiaLab Technical Specifications
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Case studies
- Production optimisation through feedback analysis
- Satisfaction questionnaire analysis
- Football World Cup 2010
- Breast Cancer Diagnostics
- Microarray analysis
- Health trajectory analysis
- Biocomputing transcriptome analysis
- Risk analysis and security policy
- Difficult intubations analysis
- Cyber-crimes detection
- Customer characterization
- Organization name identification
- Implementation of a Bayesian score
- Modeling and simulation of dynamic systems
- Analysis of a perfume market
- Consumer segmentation
- Identifying drivers of liking
- Driver Analysis: The Missing Links
- Salmonella isolation
- Political Analysis
- Studying consumer drivers
- Employees satisfaction analysis
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Resources
BayesiaLab in action: 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.
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- Driver Analysis: The Missing Links The authors of this paper highlight several shortcomings of traditional techniques for driver analysis. At the same time they illustrate how Bayesian networks can help overcome such challenges.
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Analysis of a perfume market
Applibugs 2009
Application of Probabilistic Structural Equations (PSE) to the analysis of a perfume market
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Identifying drivers of liking
Pangborn 2009
Presentation at Pangborn 2009 conference of a method to identify drivers of liking for fine fragrances with BayesiaLab (presentation by our partner Repères)
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Studying consumer drivers
Sensometrics meeting 2008 (St Catharine, Ontario)
Sensometrics meeting (St Catharine, Ontario, July 21st 2008) : studying consumer drivers with bayesian networks (in collaboration with Repères).
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Consumer segmentation
SKIM Conference 2008 (Barcelone)
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
- Microarray analysis with Bayesian Networks In this study, we turn to the field of cancer classification by means of microarray analysis. Microarray analysis is a technique for gene expression profiling of cell samples. Expression profiles indicate which genes are currently active among thousands of genes.
- Breast Cancer Diagnostics with Bayesian Networks Our white paper reevaluates the Wisconsin Breast Cancer Database within the framework of Bayesian networks, which, to our knowledge, has not been done before.
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Difficult intubations analysis
Scata 2007 (London)
Prediction of difficult intubation (DI) is crucial during pre anaesthesia assessment of a patient. Many criterions are used to predict DI with different performances. In this case study, we show how BayesiaLab, through its learning algorithms, allows to quickly discovering unknown probabilistic relationships between variables and enhance prediction.
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Salmonella isolation
20th International Pig Veterinary Society Congress, 2008, Durban (South Africa)
Identification of factors associated with Salmonella isolation on pork carcasses via bayesian networks.
- Biocomputing transcriptome analysis Bioinformatics with BayesiaLab.
- Health trajectory analysis Prediction of medical needs with BayesiaLab.
Strategy
- Football World Cup 2010 A funny game illustrating the chances of a team to qualify for the second round of the 2010 World Cup.
- Employees satisfaction analysis Application of probabilistic structural equations to find employees satisfaction drivers.
- Political Analysis Analysis of the French Presidential Elections of April 2007.
Risk management
- 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.