Examples.md

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 The data set contains 9 variables with 442 samples. The target variable for prediction in the following example is 'Depth'. The variable is also used to visually evaluate sampling quality via distribution plot.
 
-The following combinations of hyperparameters will be reviewed in this example:
+This and the next example consider the following combinations of hyperparameters used for Bayesian network learning:
 
 * K2 metric;
 * K2 metric with gaussian mixtures (GMM);
 * K2 metric with GMM and logit nodes;
 * K2 with initial structure. 
 
+All the examples are executed using cross-validation.
+
 ## K2 metric sampling example
 
 ![k2](https://user-images.githubusercontent.com/86363785/188129119-dfa62b6d-b1fd-4e63-aa75-fb7aafba95a1.png)
@@ -28,4 +30,8 @@ The following combinations of hyperparameters will be reviewed in this example:
 ![geo_k2_expert](https://user-images.githubusercontent.com/86363785/188129863-b8777153-eb31-4e8f-b8bf-b87e7c959035.png)
 
 
-# Social data example
+# Social data example
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+
+The second example is similar to the previous one, but carried out on different data set. Social data set consists of 30000 anonymous bank records with 9 variables each, bayesian networks were learnt on a sample with 2000 records. 
+
+ 
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