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Questions? Feedback? powered by Olark live chat softwareHomeBayesiaLab SoftwareKnowledge ModelingData ManagementNetwork LearningNetwork LayoutNetwork EvaluationInferenceVisual Network AnalysisNetwork Analysis ReportsOptimizationNetwork ToolsGraphing & PlottingBayesiaLab EditionsPricingBayesia ExpertKnowledge ElicitationEnvironmentBayesia Engine APIBayesia Market SimulatorTrial DownloadCourses & EventsSeptember 16-18, 2014Introductory CourseLos AngelesSeptember 19-20, 2014Causal Inference CourseLos AngelesSeptember 21-23, 2014Advanced CourseLos AngelesSeptember 23, 2014BayesiaLab User ConferenceOpening SessionSeptember 24, 2014BayesiaLab User Conference Main Conference SessionNovember 19-21, 2013Introductory CourseWashington, D.C.Tutorials & Case StudiesIntroduction to Bayesian NetworksEvidential Reasoning with Bayesian NetworksBreast Cancer DiagnosticsKnowledge Discovery in the Stock MarketCausal InferenceMarketing Mix ModelingLoyalty Driver AnalysisMicroarray AnalysisMissing Values ProcessingChoice ModelingParadoxes & FallaciesVehicle Weight, Size, and Injury RiskKey Drivers Analysis & Product OptimizationProbabilistic Latent Factor InductionFrom Bayesian Networks to Causal and Counterfactual ReasoningBlogAboutFAQHomeBayesiaLab SoftwareKnowledge ModelingData ManagementNetwork LearningNetwork LayoutNetwork EvaluationInferenceVisual Network AnalysisNetwork Analysis ReportsOptimizationNetwork ToolsGraphing & PlottingBayesiaLab EditionsPricing Bayesia ExpertKnowledge ElicitationEnvironment Bayesia Engine API Bayesia Market Simulator Trial Download Courses & Events September 16-18, 2014Introductory CourseLos Angeles September 19-20, 2014Causal Inference CourseLos Angeles September 21-23, 2014Advanced CourseLos Angeles September 23, 2014BayesiaLab User ConferenceOpening Session September 24, 2014BayesiaLab User Conference Main Conference Session November 19-21, 2013Introductory CourseWashington, D.C. Tutorials & Case Studies Introduction to Bayesian Networks Evidential Reasoning with Bayesian Networks Breast Cancer Diagnostics Knowledge Discovery in the Stock Market Causal Inference Marketing Mix Modeling Loyalty Driver Analysis Microarray Analysis Missing Values Processing Choice Modeling Paradoxes & Fallacies Vehicle Weight, Size, and Injury Risk Key Drivers Analysis & Product Optimization Probabilistic Latent Factor Induction From Bayesian Networks to Causal and Counterfactual Reasoning Blog About FAQ What is BayesiaLab? BayesiaLab 5.3 is a powerful Artificial Intelligence software (Win/Mac/Unix), which provides scientists a comprehensive “lab” environment for machine learning, knowledge modeling, analytics, simulation, and optimization — all based on the Bayesian network paradigm. BayesiaLab employs sophisticated learning algorithms to automatically generate structural models from data, making it a highly capable knowledge discovery tool. It enables applied researchers to explore high-dimensional problem dom
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