Add possibility to select target column

.gitignore

-.idea/
+*.idea/
 
 **/_env
+**/_logs
 **/embeddings
 
 *.pyc

code_mario/keras_extension.py

@@ -12,8 +12,12 @@ from util import LoggingMixin
 class KerasUtil(object):
 
     @staticmethod
-    def best_model_checkpointing(model_name: str, monitor_loss: str = "loss"):
-        best_model_file = os.path.join(AppContext.default().output_dir, "optimal_%s.h5" % model_name)
+    def best_model_checkpointing_by_model_name(model_name: str, monitor_loss: str = "loss"):
+        best_model_file = os.path.join(AppContext.default().output_dir, "%s_best.h5" % model_name)
+        return ModelCheckpoint(filepath=best_model_file, monitor=monitor_loss, save_best_only=True, verbose=1)
+
+    @staticmethod
+    def best_model_checkpointing_by_file_path(best_model_file: str, monitor_loss: str = "loss"):
         return ModelCheckpoint(filepath=best_model_file, monitor=monitor_loss, save_best_only=True, verbose=1)
 
 
@@ -59,7 +63,7 @@ class ExtendedKerasClassifier(KerasClassifier, LoggingMixin):
         else:
             self.logger.debug("Model wasn't re-fitted -> re-using existing model")
             pass
-
+        self.logger.info("Classifer has %s classes", len(self.classes_))
         return super(ExtendedKerasClassifier, self).predict(x, **kwargs)
 
     def __getstate__(self):

code_mario/preprocessing.py

@@ -20,6 +20,13 @@ class DataPreparationUtil(object):
 
         return MapFunction(column, _lower)
 
+    @staticmethod
+    def strip(column: str):
+        def _strip(text):
+            return str(text).strip()
+
+        return MapFunction(column, _strip)
+
     @staticmethod
     def tokenize(text_column: str, token_column: str = "tokens"):
         return SimpleTokenizer(text_column, token_column)
@@ -57,6 +64,20 @@ class DataPreparationUtil(object):
 
         return MapFunction(icd10_column, _extract, target_column)
 
+    @staticmethod
+    def extract_icd10_section(icd10_column: str, target_column: str):
+        def _extract(value):
+            return value.strip()[0:2].lower()
+
+        return MapFunction(icd10_column, _extract, target_column)
+
+    @staticmethod
+    def extract_icd10_subsection(icd10_column: str, target_column: str):
+        def _extract(value):
+            return value.strip()[0:3].lower()
+
+        return MapFunction(icd10_column, _extract, target_column)
+
     @staticmethod
     def extract_icd10_subchapter(icd10_column: str, target_column: str):
         def _extract(value):

requirements.txt

@@ -7,3 +7,4 @@ sklearn
 tensorflow
 tqdm
 h5py
+cython