Examples.md

@@ -7,7 +7,19 @@ Both examples consider the following combinations of hyperparameters used for Ba
 * K2 metric with GMM and logit nodes;
 * K2 with initial structure. 
 
-All the examples are executed using cross-validation.
+All the examples are executed using cross-validation, the data is preproccesed as follows: 
+
+~~~python
+data.dropna(inplace=True)
+data.reset_index(inplace=True, drop=True)
+
+encoder = preprocessing.LabelEncoder()
+discretizer = preprocessing.KBinsDiscretizer(n_bins=5, encode='ordinal', strategy='quantile')
+
+p = pp.Preprocessor([('encoder', encoder), ('discretizer', discretizer)])
+
+discretized_data, est = p.apply(train)
+~~~
 
 # Geological data example
 
@@ -19,18 +31,58 @@ The data set contains 9 variables with 442 samples. The target variable for pred
 
 ### K2 metric sampling example
 
+To sample using K2 metric the following code can be used:
+
+~~~python
+train, validation = train_test_split(data, test_size=0.1)
+bn = Nets.HybridBN(has_logit=False, use_mixture=False)
+bn.add_nodes(info)
+bn.add_edges(discretized_data,  scoring_function=('K2',K2Score))
+bn.fit_parameters(train)
+# prediction
+val_pred = bn.predict(validation.iloc[:,:8], 5)
+# sampling
+sample = bn.sample(5000, parall_count=5)
+~~~
+
 <img width="353" alt="K2 geo" src="https://user-images.githubusercontent.com/86363785/188191005-45898257-ff57-4a5c-ba6c-1012c28e689e.png">
 
 ![k2](https://user-images.githubusercontent.com/86363785/188129119-dfa62b6d-b1fd-4e63-aa75-fb7aafba95a1.png)
 
 ### Sampling with K2 + GMM example
 
+To sample using K2 with GMM the following code can be used:
+
+~~~python
+train, validation = train_test_split(data, test_size=0.1)
+bn = Nets.HybridBN(has_logit=False, use_mixture=True)
+bn.add_nodes(info)
+bn.add_edges(discretized_data,  scoring_function=('K2',K2Score))
+bn.fit_parameters(train)
+# prediction
+val_pred = bn.predict(validation.iloc[:,:8], 5)
+# sampling
+sample = bn.sample(5000, parall_count=5)
+~~~
+
 <img width="566" alt="K2 + GMM geo" src="https://user-images.githubusercontent.com/86363785/188191226-4c7c3e7a-d91a-4c43-81b5-39698c87c0b8.png">
 
 ![geo_k2_gmm](https://user-images.githubusercontent.com/86363785/188129748-ce239eb4-bbab-43f0-9d80-c92483f27613.png)
 
 ### Sampling with K2 + GMM + logit nodes example
 
+~~~python
+train, validation = train_test_split(data, test_size=0.1)
+bn = Nets.HybridBN(has_logit=True, use_mixture=False)
+bn.add_nodes(info)
+bn.add_edges(discretized_data,  scoring_function=('K2',K2Score))
+bn.fit_parameters(train)
+# prediction
+val_pred = bn.predict(validation.iloc[:,:8], 5)
+# sampling
+sample = bn.sample(5000, parall_count=5)
+~~~
+
 <img width="637" alt="K2 + gmm + logit geo" src="https://user-images.githubusercontent.com/86363785/188191300-759aa54d-3d2e-4b50-80d5-7fa7347e557f.png">
 
 ![geo_k2_gmm_logit](https://user-images.githubusercontent.com/86363785/188129774-a3695199-776d-493f-8a9c-bf78125f03fb.png)