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BayesiaLab 7.0: New Features & Updates (10/2017)

Here is a small selection of new or updated features released in BayesiaLab 7.0:

  • Using Confidence Intervals, you can analyze the estimated (conditional) distributions of your machine-learned networks.
  • Resampling allows you to measure the variability of your estimations with Jackknife, Data Perturbation and Bootstrap, as well as the quality of your learning configurations with K-Fold.  
  • You can examine your Bayesian network models in three dimensions with the new 3D Mapping tool.
  • You can now leverage the power and flexibility of Function Nodes with BayesiaLab's optimization tools.
  • GIS Mapping allows you to visualize your data and inference results on Google maps.
  • New options are available for Data Clustering, including Heterogeneity, Multi-Net, and Random Weights, which help you find better solutions for data segmentation tasks.

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