About-BAMT-algorithms.md

@@ -5,7 +5,7 @@ Web-BAMT is a web service that allows you to train Bayesian networks on demonstr
 A Bayesian network is a pair of directed acyclic graph (DAG) describing the dependencies of characteristics and some factorization of the joint distribution of characteristics in the product of conditional, generated by these dependencies. 
 The task of training a Bayesian network is thus split into two subtasks:
 * Finding the structure of the Bayesian network.
-* Parametric training of the Bayesian network or, in other words, selection of marginal and conditional distributions that describe the conditional ones accurately enough.
+* Parametric learning of the Bayesian network or, in other words, selection of marginal and conditional distributions that describe the conditional ones accurately enough.
 
 # Structural learning algorithms for a Bayesian network
 Often the task of constructing a network is reduced to optimization. In the DAG space, score functions are introduced that evaluate how well the graph describes the dependencies between features. Web BAMT uses the Hill-Climbing algorithm to search in this space.