Converting a noisy-or Bayes model to Aster analytic function model
Greetings to all the data scientists / Aster fans from the forum,
I am trying to convert a Healthcare Knowledge Model derived from anonymized electronic patient records that was created though nosiy-or Bayes modelling to a similar model that could be used by one of the Aster analytic functions (since the original comes from text processing I thought at a first glance to use NaiveBayesTextPrediction....but things are not so similar). The model is expressed as a graph with nodes, edges and weights athttps://github.com/clinicalml/HealthKnowledgeGraph.
Compared to Aster Naive Bayes Text Prediction based on a Bernoulli model this one is a little bit different since the NBTP requires prior probabilities and the weights are in a total different range (for those who have queryed a model table from Naive Bayes Text Prediction there is an additional line that described the prior probability for the class on top of the tokens probabilities). The noisy-or matrix I am struggling with looks like: