BayesiaLab 5.3: New Features & Updates (03/2014)

Here is a small selection of the new or updated features released in BayesiaLab 5.3:

• Redesigned: Contribution Analysis uses counterfactuals to measure the “added value” of individual driver on the target variable.
• Conditional Probability Trees can take advantage of contextual independencies in the parent-to-child relationships.
• Targeted Evaluation can now be performed with a limited number of questions.
• Markov Blanket Export in Visual Basic.
• Evidence Data Weighting for using the set of Evidence defined on the current network to compute a weight for each row of the data set.
• New missing values processing with Entropy-Based Imputations and Most Probable Explanation Imputations.
• Tree Discretization using Structural Coefficients.
• Search Function in Settings.