Updated paths

.gitignore

-./gen_train_data/input
-./gen_train_data/output
-./EDA/input
+gen_train_data/input/
+gen_train_data/output/
+EDA/input/
\ No newline at end of file

gen_train_data/gen_train_data.ipynb

@@ -36,8 +36,8 @@
    "outputs": [],
    "source": [
     "# Load clean datasets\n",
-    "df_pre = pd.read_csv('./data/input/pre_dataset.csv')\n",
-    "df_post = pd.read_csv('./data/input/post_dataset.csv')"
+    "df_pre = pd.read_csv('./input/pre_dataset.csv')\n",
+    "df_post = pd.read_csv('./input/post_dataset.csv')"
    ]
   },
   {
@@ -95,10 +95,10 @@
    "outputs": [],
    "source": [
     "# Save test data\n",
-    "np.save('./data/output/pre/X_test_pre.npy', X_test_pre)\n",
-    "np.save('./data/output/pre/y_test_pre.npy', y_test_pre)\n",
-    "np.save('./data/output/post/X_test_post.npy', X_test_post)\n",
-    "np.save('./data/output/post/y_test_post.npy', y_test_post)"
+    "np.save('./output/pre/X_test_pre.npy', X_test_pre)\n",
+    "np.save('./output/pre/y_test_pre.npy', y_test_pre)\n",
+    "np.save('./output/post/X_test_post.npy', X_test_post)\n",
+    "np.save('./output/post/y_test_post.npy', y_test_post)"
    ]
   },
   {
@@ -108,10 +108,10 @@
    "outputs": [],
    "source": [
     "# Save ORIGINAL training data\n",
-    "np.save('./data/output/pre/X_train_pre.npy', X_train_pre)\n",
-    "np.save('./data/output/pre/y_train_pre.npy', y_train_pre)\n",
-    "np.save('./data/output/post/X_train_post.npy', X_train_post)\n",
-    "np.save('./data/output/post/y_train_post.npy', y_train_post)"
+    "np.save('./output/pre/X_train_pre.npy', X_train_pre)\n",
+    "np.save('./output/pre/y_train_pre.npy', y_train_pre)\n",
+    "np.save('./output/post/X_train_post.npy', X_train_post)\n",
+    "np.save('./output/post/y_train_post.npy', y_train_post)"
    ]
   },
   {
@@ -133,10 +133,10 @@
    "outputs": [],
    "source": [
     "# Save oversampled training data\n",
-    "np.save('./data/output/pre/X_train_over_pre.npy', X_train_over_pre)\n",
-    "np.save('./data/output/pre/y_train_over_pre.npy', y_train_over_pre)\n",
-    "np.save('./data/output/post/X_train_over_post.npy', X_train_over_post)\n",
-    "np.save('./data/output/post/y_train_over_post.npy', y_train_over_post)"
+    "np.save('./output/pre/X_train_over_pre.npy', X_train_over_pre)\n",
+    "np.save('./output/pre/y_train_over_pre.npy', y_train_over_pre)\n",
+    "np.save('./output/post/X_train_over_post.npy', X_train_over_post)\n",
+    "np.save('./output/post/y_train_over_post.npy', y_train_over_post)"
    ]
   },
   {
@@ -158,10 +158,10 @@
    "outputs": [],
    "source": [
     "# Save undersampled training data\n",
-    "np.save('./data/output/pre/X_train_under_pre.npy', X_train_under_pre)\n",
-    "np.save('./data/output/pre/y_train_under_pre.npy', y_train_under_pre)\n",
-    "np.save('./data/output/post/X_train_under_post.npy', X_train_under_post)\n",
-    "np.save('./data/output/post/y_train_under_post.npy', y_train_under_post)"
+    "np.save('./output/pre/X_train_under_pre.npy', X_train_under_pre)\n",
+    "np.save('./output/pre/y_train_under_pre.npy', y_train_under_pre)\n",
+    "np.save('./output/post/X_train_under_post.npy', X_train_under_post)\n",
+    "np.save('./output/post/y_train_under_post.npy', y_train_under_post)"
    ]
   },
   {
@@ -171,7 +171,7 @@
    "outputs": [],
    "source": [
     "# Save features\n",
-    "np.save('./data/output/attributes.npy', feat)"
+    "np.save('./output/attributes.npy', feat)"
    ]
   }
  ],