diff --git a/data/boat.csv b/data/boat.csv
index b329a62..0f07ebf 100644
--- a/data/boat.csv
+++ b/data/boat.csv
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diff --git a/data/boat.json b/data/boat.json
index 5de5ce7..51050a9 100644
--- a/data/boat.json
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diff --git a/data/boat.txt b/data/boat.txt
index 7846b35..38e523a 100644
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diff --git a/examples/core/create_node.py b/examples/core/create_node.py
index ef9bbed..fcc9574 100644
--- a/examples/core/create_node.py
+++ b/examples/core/create_node.py
@@ -4,7 +4,7 @@
 
 # Defining index, label and features
 idx = 0
-label = 1
+label = 0
 features = np.asarray([2, 2.5, 1.5, 4])
 
 # Creating a Node
diff --git a/examples/math/general_purpose.py b/examples/math/general_purpose.py
index f93491b..1e4e008 100644
--- a/examples/math/general_purpose.py
+++ b/examples/math/general_purpose.py
@@ -4,8 +4,8 @@
 
 # Defining array, labels and predictions
 array = np.asarray([1.5, 2, 0.5, 1.25, 1.75, 3])
-labels = [1, 1, 1, 2, 2, 2, 3]
-preds = [1, 1, 2, 2, 1, 2, 3]
+labels = [0, 0, 0, 1, 1, 1, 2]
+preds = [0, 0, 1, 1, 0, 1, 2]
 
 # Normalizing the array
 norm_array = g.normalize(array)
diff --git a/opfython/core/node.py b/opfython/core/node.py
index 0edab0f..0aeb4ec 100644
--- a/opfython/core/node.py
+++ b/opfython/core/node.py
@@ -15,7 +15,7 @@ class Node:
 
     """
 
-    def __init__(self, idx=0, label=1, features=None):
+    def __init__(self, idx=0, label=0, features=None):
         """Initialization method.
 
         Args:
@@ -96,8 +96,8 @@ def label(self):
     def label(self, label):
         if not isinstance(label, int):
             raise e.TypeError('`label` should be an integer')
-        if label < 1:
-            raise e.ValueError('`label` should be >= 1')
+        if label < 0:
+            raise e.ValueError('`label` should be >= 0')
 
         self._label = label
 
@@ -272,8 +272,7 @@ def pred(self, pred):
         if not isinstance(pred, int):
             raise e.TypeError('`pred` should be an integer')
         if pred < c.NIL:
-            raise e.ValueError(
-                '`pred` should have a value larger than `NIL`, e.g., -1')
+            raise e.ValueError('`pred` should have a value larger than `NIL`, e.g., -1')
 
         self._pred = pred
 
@@ -288,7 +287,6 @@ def relevant(self):
     @relevant.setter
     def relevant(self, relevant):
         if relevant not in [c.RELEVANT, c.IRRELEVANT]:
-            raise e.TypeError(
-                '`relevant` should be `RELEVANT` or `IRRELEVANT`')
+            raise e.TypeError('`relevant` should be `RELEVANT` or `IRRELEVANT`')
 
         self._relevant = relevant
diff --git a/opfython/math/general.py b/opfython/math/general.py
index d3512e1..3ced4b2 100644
--- a/opfython/math/general.py
+++ b/opfython/math/general.py
@@ -26,7 +26,7 @@ def confusion_matrix(labels, preds):
     preds = np.asarray(preds)
 
     # Calculating the number of classes
-    n_class = np.max(labels)
+    n_class = np.max(labels) + 1
 
     # Creating an empty errors matrix
     c_matrix = np.zeros((n_class, n_class))
@@ -34,7 +34,7 @@ def confusion_matrix(labels, preds):
     # For every label and prediction
     for label, pred in zip(labels, preds):
         # Increments the corresponding cell from the confusion matrix
-        c_matrix[label - 1][pred - 1] += 1
+        c_matrix[label][pred] += 1
 
     return c_matrix
 
@@ -77,21 +77,21 @@ def opf_accuracy(labels, preds):
     preds = np.asarray(preds)
 
     # Calculating the number of classes
-    n_class = np.max(labels)
+    n_class = np.max(labels) + 1
 
     # Creating an empty errors matrix
     errors = np.zeros((n_class, 2))
 
     # Gathering the amount of labels per class
-    counts = np.bincount(labels)[1:]
+    counts = np.bincount(labels)
 
     # For every label and prediction
     for label, pred in zip(labels, preds):
         # If label is different from prediction
         if label != pred:
             # Increments the corresponding cells from the error matrix
-            errors[pred - 1][0] += 1
-            errors[label - 1][1] += 1
+            errors[pred][0] += 1
+            errors[label][1] += 1
 
     # Calculating the float value of the true label errors
     errors[:, 1] /= counts
@@ -125,7 +125,7 @@ def opf_accuracy_per_label(labels, preds):
     preds = np.asarray(preds)
 
     # Calculating the number of classes
-    n_class = np.max(labels)
+    n_class = np.max(labels) + 1
 
     # Creating an empty errors array
     errors = np.zeros(n_class)
@@ -138,7 +138,7 @@ def opf_accuracy_per_label(labels, preds):
         # If label is different from prediction
         if label != pred:
             # Increments the corresponding cell from the error array
-            errors[label - 1] += 1
+            errors[label] += 1
 
     # Calculating the float value of the true label errors
     errors /= counts
diff --git a/opfython/models/semi_supervised.py b/opfython/models/semi_supervised.py
index 3b9af70..8025e04 100644
--- a/opfython/models/semi_supervised.py
+++ b/opfython/models/semi_supervised.py
@@ -67,7 +67,7 @@ def fit(self, X_train, Y_train, X_unlabeled, I_train=None):
         # Iterate over every possible unlabeled sample
         for i, feature in enumerate(X_unlabeled):
             # Creates a Node structure
-            node = Node(current_n_nodes + i, 1, feature)
+            node = Node(current_n_nodes + i, 0, feature)
 
             # Appends the node to the list
             self.subgraph.nodes.append(node)
diff --git a/opfython/stream/parser.py b/opfython/stream/parser.py
index a096b50..f8a1deb 100644
--- a/opfython/stream/parser.py
+++ b/opfython/stream/parser.py
@@ -40,10 +40,10 @@ def parse_loader(data):
                 'Parsed data should have at least two distinct labels')
 
         # If there are unsequential labels
-        if len(counts) != np.max(Y):
+        if len(counts) != (np.max(Y) + 1):
             # Raises a ValueError
             raise e.ValueError(
-                'Parsed data should have sequential labels, e.g., 1, 2, ..., n')
+                'Parsed data should have sequential labels, e.g., 0, 1, ..., n-1')
 
         logger.info('Data parsed.')
 
diff --git a/opfython/utils/converter.py b/opfython/utils/converter.py
index 61c0400..3f8fb43 100644
--- a/opfython/utils/converter.py
+++ b/opfython/utils/converter.py
@@ -57,7 +57,8 @@ def opf2txt(opf_path, output_file=None):
             data = struct.unpack(file_format, f.read(data_size))
 
             # Appending the data to list
-            samples.append(data)
+            # Note that we subtract 1 from `labels` column
+            samples.append((data[0], data[1] - 1, *data[2:]))
 
     # Closing opf file
     f.close()
@@ -119,7 +120,8 @@ def opf2csv(opf_path, output_file=None):
             data = struct.unpack(file_format, f.read(data_size))
 
             # Appending the data to list
-            samples.append(data)
+            # Note that we subtract 1 from `labels` column
+            samples.append((data[0], data[1] - 1, *data[2:]))
 
     # Closing opf file
     f.close()
@@ -185,7 +187,7 @@ def opf2json(opf_path, output_file=None):
             # Appending the data to JSON structure
             json['data'].append({
                 'id': data[0],
-                'label': data[1],
+                'label': data[1] - 1,
                 'features': list(data[2:])
             })
 
diff --git a/tests/opfython/core/test_node.py b/tests/opfython/core/test_node.py
index 3b5a97f..ccc6bd8 100644
--- a/tests/opfython/core/test_node.py
+++ b/tests/opfython/core/test_node.py
@@ -31,7 +31,7 @@ def test_node_idx_setter():
 def test_node_label():
     n = node.Node()
 
-    assert n.label == 1
+    assert n.label == 0
 
 
 def test_node_label_setter():
@@ -45,7 +45,7 @@ def test_node_label_setter():
     assert n.label == 1
 
     try:
-        n.label = 0
+        n.label = -1
     except:
         n.label = 1
 
diff --git a/tests/opfython/math/test_general.py b/tests/opfython/math/test_general.py
index 0200e9c..ade1526 100644
--- a/tests/opfython/math/test_general.py
+++ b/tests/opfython/math/test_general.py
@@ -3,8 +3,8 @@
 
 
 def test_confusion_matrix():
-    labels = [1, 1, 2, 2]
-    preds = [1, 1, 2, 2]
+    labels = [0, 0, 1, 1]
+    preds = [0, 0, 1, 1]
 
     c_matrix = general.confusion_matrix(labels, preds)
 
@@ -20,8 +20,8 @@ def test_normalize():
 
 
 def test_opf_accuracy():
-    labels = [1, 1, 2, 2]
-    preds = [1, 1, 1, 1]
+    labels = [0, 0, 1, 1]
+    preds = [0, 0, 0, 0]
 
     acc = general.opf_accuracy(labels, preds)
 
@@ -29,8 +29,8 @@ def test_opf_accuracy():
 
 
 def test_opf_accuracy_per_label():
-    labels = [1, 1, 2, 2]
-    preds = [1, 1, 1, 1]
+    labels = [0, 0, 1, 1]
+    preds = [0, 0, 0, 0]
 
     acc_per_label = general.opf_accuracy_per_label(labels, preds)
 
@@ -48,8 +48,8 @@ def test_opf_pre_compute_distances():
 
 
 def test_purity():
-    labels = [1, 1, 2, 2]
-    preds = [1, 1, 2, 2]
+    labels = [0, 0, 1, 1]
+    preds = [0, 0, 1, 1]
 
     purity = general.purity(labels, preds)
 
diff --git a/tests/opfython/models/test_unsupervised.py b/tests/opfython/models/test_unsupervised.py
index c127845..a18d4a7 100644
--- a/tests/opfython/models/test_unsupervised.py
+++ b/tests/opfython/models/test_unsupervised.py
@@ -121,4 +121,4 @@ def test_unsupervised_opf_propagate_labels():
 
     opf.propagate_labels()
 
-    assert opf.subgraph.nodes[0].predicted_label == 1
+    assert opf.subgraph.nodes[0].predicted_label == 0