modfied no header for labels csv output

Author: ptyadana

ML - Applied Machine Learning - Algorithms/01.Review of Foundation/02.Foundations - Split data into train, validation, and test set.ipynb

@@ -171,7 +171,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -198,17 +198,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
     "X_train.to_csv('../Data/train_features.csv', index=False)\n",
     "X_val.to_csv('../Data/val_features.csv', index=False)\n",
     "X_test.to_csv('../Data/test_features.csv', index=False)\n",
     "\n",
-    "y_train.to_csv('../Data/train_labels.csv', index=False)\n",
-    "y_val.to_csv('../Data/val_labels.csv', index=False)\n",
-    "y_test.to_csv('../Data/test_labels.csv', index=False)"
+    "y_train.to_csv('../Data/train_labels.csv', index=False, header=False)\n",
+    "y_val.to_csv('../Data/val_labels.csv', index=False, header=False)\n",
+    "y_test.to_csv('../Data/test_labels.csv', index=False, header=False)"
    ]
   },
   {

ML - Applied Machine Learning - Algorithms/Data/test_labels.csv

@@ -1,4 +1,3 @@
-Survived
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 0
 0

ML - Applied Machine Learning - Algorithms/Data/train_labels.csv

@@ -1,4 +1,3 @@
-Survived
 1
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 1

ML - Applied Machine Learning - Algorithms/Data/val_labels.csv

@@ -1,4 +1,3 @@
-Survived
 1
 0
 0