diff --git a/IngeoDash/annotate.py b/IngeoDash/annotate.py
index 96c797f..797fca6 100644
--- a/IngeoDash/annotate.py
+++ b/IngeoDash/annotate.py
@@ -27,7 +27,7 @@ def has_label(mem: Config, x):
     return False
 
 
-def model(mem: Config, data: dict, select: bool=True):
+def model(mem: Config, data: dict):
     lang = mem[mem.lang]
     if lang not in CONFIG.denseBoW:
         dense = DenseBoW(lang=lang, voc_size_exponent=mem.voc_size_exponent,
@@ -41,7 +41,7 @@ def model(mem: Config, data: dict, select: bool=True):
                      n_jobs=mem.n_jobs,
                      dataset=False, emoji=False, keyword=False)
     dense.text_representations_extend(CONFIG.denseBoW[lang])
-    if select:
+    if mem.dense_select:
         dense.select(D=data)
     _ = np.unique([x[mem.label_header] for x in data],
                   return_counts=True)[1]
@@ -78,7 +78,7 @@ def active_learning_selection(mem: Config):
     data = []
     for cnt, i in enumerate(index):
         ele = D.pop(i - cnt)
-        ele[mem.label_header] = klasses[cnt]
+        ele[mem.label_header] = ele.get(mem.label_header, klasses[cnt])
         data.append(ele)
     db[mem.original] = D
     db[mem.data] = data
diff --git a/IngeoDash/config.py b/IngeoDash/config.py
index 5a00f6f..b47c2e5 100644
--- a/IngeoDash/config.py
+++ b/IngeoDash/config.py
@@ -53,6 +53,7 @@ class Config:
     voc_selection: str='most_common_by_type'
     estimator_class: object=LinearSVC
     decision_function_name: str='decision_function'
+    dense_select: bool=True
 
 
     def __getitem__(self, key):
@@ -67,7 +68,8 @@ def __call__(self, value):
             cls.mem = json.loads(value) if isinstance(value, str) else value
         for key in ['label_header', 'text', 'n_value',
                     'voc_size_exponent', 'voc_selection',
-                    'estimator_class', 'decision_function_name']:
+                    'estimator_class', 'decision_function_name',
+                    'dense_select']:
             if key in cls.mem:
                 setattr(cls, key, cls.mem[key])
         return cls
diff --git a/IngeoDash/tests/test_config.py b/IngeoDash/tests/test_config.py
index 31f5b87..b0210b9 100644
--- a/IngeoDash/tests/test_config.py
+++ b/IngeoDash/tests/test_config.py
@@ -50,7 +50,8 @@ def test_Config():
                    voc_size_exponent=15,
                    voc_selection='most_common_by_type',
                    estimator_class=LinearSVC,
-                   decision_function_name='decision_function')
+                   decision_function_name='decision_function',
+                   dense_select=True)
     for k, v in default.items():
         assert v == getattr(conf, k)
 
@@ -75,15 +76,16 @@ def test_Config_call():
 
 
 def test_Config_call2():
-    mem = CONFIG(dict(label_header='label',
-                      text='texto', n_value=12,
-                      voc_size_exponent=15,
-                      voc_selection='most_common_by_type',
-                      estimator_class=LinearSVC,
-                      decision_function_name='decision_function'))
-    assert mem.label_header == 'label'
-    assert mem.text == 'texto'
-    assert mem.n_value == 12
+    kwargs = dict(label_header='label',
+                  text='texto', n_value=12,
+                  voc_size_exponent=15,
+                  voc_selection='most_common_by_type',
+                  estimator_class=LinearSVC,
+                  decision_function_name='decision_function',
+                  dense_select=True)
+    mem = CONFIG(kwargs)
+    for k, v in kwargs.items():
+        assert getattr(mem, k) == v
 
 
 def test_CONFIG():