BayesiaLab 5.3 released today!
BayesiaLab 5.3 is a powerful desktop application with a highly sophisticated graphical user interface, which provides scientists a comprehensive “lab” environment for machine learning, knowledge modeling, diagnosis, analysis, simulation, and optimization.
With the launch of BayesiaLab 1.0 in 2001, using Bayesian networks has become practically feasible for applied researchers, enabling them to gain deep understanding of high-dimensional domains. BayesiaLab leverages the inherently graphical structure of Bayesian networks for exploring and explaining complex problems. Also, among all analytics software packages, BayesiaLab is unique in its ability to formally distinguish between observational and causal inference.
A Bayesian network is a type of mathematical model that can simultaneously represent a multitude of relationships between variables in a system. The graph of a Bayesian network contains nodes (representing variables) and directed arcs that link the nodes. The arcs represent the relationships of the nodes.
Whereas traditional statistical models are of the form y=f(x), Bayesian networks do not have to distinguish between independent and dependent variables. Rather, a Bayesian network approximates the entire joint probability distribution of the system under study.
This allows the researcher to carry out "omnidirectional inference," i.e. to reason from cause to effect (simulation), or from effect to cause (diagnosis), all within the same model.
BayesiaLab is built on the foundation of the Bayesian network formalism (perhaps in the same way as a spreadsheet program would be based on arithmetics).
BayesiaLab can generate Bayesian networks from human knowledge and/or by machine learning from data. The Bayesian network thus become as compact model of the underlying - and often high-dimensional - problem domain.
Based on this network model, BayesiaLab provides a wide range of analysis, simulation and optimization functions that allow the researcher to exploit all the dynamics captured in the network.
Everything you need to know about Bayesian networks and BayesiaLab on two pages. This document highlights the key features of BayesiaLab. At a glance, business executives and decision makers can see BayesiaLab's unique value proposition with regard to research and analytics.
Market research stands out as a quintessential use case for the BayesiaLab software platform. BayesiaLab is the only research tool that allows you to model markets, consumers, and products, in all their dimensions, in a single, universal and highly-transparent model.
American Diabetic Association
Booz Allen Hamilton
Cancer Care Ontario
Électricité de France
Geisinger Health System
George Washington University
Indian Institute of Management Bangalore
InterContinental Hotels Group
Lieberman Research Worldwide
Louisiana State University
Nanyang Technological University
PSA Peugeot Citroën
The Pert Group
The Martin Agency
University of Maryland
University of Toronto
University of Virginia
BayesiaLab 5.2 Professional Edition